This document summarizes a research study that compared two optimization algorithms, Symbiotic Organisms Search (SOS) and Particle Swarm Optimization (PSO), for solving a vehicle routing problem with time windows (VRPTW) as a case study to determine the most cost-effective distribution method for a central kitchen supplying multiple outlets. The study developed a VRPTW model to minimize distribution costs by considering vehicle capacities and time windows for delivering to each customer. The algorithms were applied to route design options for the central kitchen currently considering changing to a milk-run distribution approach from the current method.
Internship report on manpower demand simulator at APL Logisticsshashi ranjan
This document summarizes an internship report on developing a manpower demand simulator tool for APL Logistics India. The tool calculates the optimal level of permanent employees required in a warehouse to perform all logistics activities at minimum cost. It does this by simulating hourly work volumes based on their probabilistic distributions and employees' productivity levels. The tool was created using VBA in Excel and can calculate manpower needs for an entire year with just over an hour of runtime.
Evaluation of Warehouse Management of COATS Bangladesh LtdS. M Zabed
This document discusses an internship report submitted by S.M. Zabed evaluating the warehouse management of COATS Bangladesh Ltd. It includes an introduction, objectives, research methodology, literature review and table of contents. The report was submitted to fulfill requirements for an MBA program at Jagannath University. It evaluates the warehouse operations and management of COATS Bangladesh Ltd to identify any issues or areas for improvement.
The document discusses challenges in warehouse operations for the retail industry based on a study conducted at Pantaloons. It finds issues like lack of manpower and space in the warehouse, as well as time constraints for staff. Some staff are well-trained in replenishment procedures while others need more training. Overall, implementing an effective warehouse management system is important to address challenges, improve customer service and supply chain efficiency.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms.
Jun, Je-Jin has over 30 years of experience in the petrochemical industry, holding roles in strategic planning, business development, marketing, and senior management. He has a bachelor's degree in chemical engineering and is fluent in English with intermediate proficiency in Chinese, Japanese, and Arabic. Notable experiences include serving as DCEO/COO of Jurong Aromatics Corporation in Singapore and leading marketing, sourcing, and new business development teams in South Korea and the Middle East. His core competencies include strategic planning, global business experience, organizational management, and successfully executing M&A deals and new projects.
This document is the 34th annual report of NTPC Ltd for the year 2009-2010. It provides information on NTPC's vision, core values, corporate mission and objectives. The report summarizes NTPC's financial and operational performance for the year including generation from different power stations. It also provides details on the company's directors and senior management, subsidiaries, accounting policies and audited financial statements. The report aims to give shareholders an overview of NTPC's activities and achievements for the fiscal year 2009-2010.
Internship report on manpower demand simulator at APL Logisticsshashi ranjan
This document summarizes an internship report on developing a manpower demand simulator tool for APL Logistics India. The tool calculates the optimal level of permanent employees required in a warehouse to perform all logistics activities at minimum cost. It does this by simulating hourly work volumes based on their probabilistic distributions and employees' productivity levels. The tool was created using VBA in Excel and can calculate manpower needs for an entire year with just over an hour of runtime.
Evaluation of Warehouse Management of COATS Bangladesh LtdS. M Zabed
This document discusses an internship report submitted by S.M. Zabed evaluating the warehouse management of COATS Bangladesh Ltd. It includes an introduction, objectives, research methodology, literature review and table of contents. The report was submitted to fulfill requirements for an MBA program at Jagannath University. It evaluates the warehouse operations and management of COATS Bangladesh Ltd to identify any issues or areas for improvement.
The document discusses challenges in warehouse operations for the retail industry based on a study conducted at Pantaloons. It finds issues like lack of manpower and space in the warehouse, as well as time constraints for staff. Some staff are well-trained in replenishment procedures while others need more training. Overall, implementing an effective warehouse management system is important to address challenges, improve customer service and supply chain efficiency.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms.
Jun, Je-Jin has over 30 years of experience in the petrochemical industry, holding roles in strategic planning, business development, marketing, and senior management. He has a bachelor's degree in chemical engineering and is fluent in English with intermediate proficiency in Chinese, Japanese, and Arabic. Notable experiences include serving as DCEO/COO of Jurong Aromatics Corporation in Singapore and leading marketing, sourcing, and new business development teams in South Korea and the Middle East. His core competencies include strategic planning, global business experience, organizational management, and successfully executing M&A deals and new projects.
This document is the 34th annual report of NTPC Ltd for the year 2009-2010. It provides information on NTPC's vision, core values, corporate mission and objectives. The report summarizes NTPC's financial and operational performance for the year including generation from different power stations. It also provides details on the company's directors and senior management, subsidiaries, accounting policies and audited financial statements. The report aims to give shareholders an overview of NTPC's activities and achievements for the fiscal year 2009-2010.
which supply chain strategies can guarantee higher manufacturer’s operational...INFOGAIN PUBLICATION
Due to the fact that scientists and practitioners alike have interested on the leveraging manufacturing companies’ operational performance, this research examined which supply chain strategies promise manufacturers higher operational performance. Later on, we clarified whether suitable resources can play an important role in the mentioned causal relationshipsas a moderator and improve the impact of the strategies on operational performance. This study is a descriptive-exploratory research in which primary data was collected from 80 Malaysian manufacturing companies. Bivariate Correlation and Multiple Regression in SPSS was applied for analyzing data. Output showed that many suppliers, few suppliers, and keiretsu network strategies enable manufacturers to achieve satisfactory level of operational performance; but, vertical integration. More importantly, suitable resources can leverage the effect of just vertical integration strategy on operational performance.
Internship PPT - The Effectiveness of Logistics and Distribution - DTDC CouriersAvinash Heston
The document presents a project on evaluating the effectiveness of logistics, distribution, and customer satisfaction at DTDC, a leading courier service company in India. The project aims to understand DTDC's position in the market, problems in international and domestic segments, and customer satisfaction levels. It will research revenue in logistics/distribution, customer reach and reaction, and issues in distribution. The design involves interacting with employees through meetings, discussions, and questionnaires. Learning points are that logistics is an important intermediary sector, customer relations are key, and flexibility according to customer needs is important in service businesses.
Heineken uses a Product-Service System (PSS) business model that is product-oriented and focused on creating value. The company's sustainability program called "Brewing a Better World" integrates sustainability into its strategy. This includes making the supply chain more sustainable by helping suppliers, especially in Africa, become more efficient and adopt practices like new seed varieties. It also focuses on reducing resources used in brewing like water, CO2 emissions, and electricity through initiatives like its Total Productive Maintenance Program. While Heineken works to build sustainable supplier relationships, it could better communicate and market these efforts to increase visibility and trust with stakeholders.
FMCG Sector analysis, Porter five model in fmcg sector, company analysis of ITC Ltd., Business model of ITC-Ltd, Function of HR Manager, Type of Training in ITC Ltd., Performance management cycle of itc ltd. Employee benefit provided in ITC Ltd.
Customer overview of retail outlets hpcl vs. reliance Supa Buoy
Hi Friends
This is supa bouy
I am a mentor, Friend for all Management Aspirants, Any query related to anything in Management, Do write me @ supabuoy@gmail.com.
I will try to assist the best way I can.
Cheers to lyf…!!!
Supa Bouy
Competitive Analysis - Literature Review of Analytical FrameworksLanguage Explore
The PLC is not the businessman's panacea but it can be useful if used in combination with other models and frameworks and alongside good management judgement.
The BCG assumed that market share is a good indicator of cash requirement though in reality, profits and cash flow depended on a lot other things than just market share and growth.
Porter who was convinced that the BCG Matrix by itself was not very useful in determining strategy for a particular business and was too simplistic, proposed some analytical tools and techniques in his three core concepts of the Basic Competitive Forces, the Generic Competitive Strategies and the Value Chain.
The document provides an overview of Samsung's history and operations in India. It details Samsung's entry into the Indian market in 1995 and its subsequent expansion, including establishing manufacturing facilities and R&D centers. It also outlines Samsung's product portfolio, core values and vision, and some of its key achievements in India such as becoming the largest mobile brand and a leader in product categories like LED TVs and refrigerators.
This document discusses using data envelopment analysis (DEA) and neural networks to model the performance of business schools in India. DEA was used to evaluate the efficiency of 49 Indian business schools based on their inputs and outputs. The average efficiency score was 0.625 using the CCR model and 0.888 using the BCC model. Neural networks were then used to predict efficiency scores when inputs change, allowing schools to generate "what if" scenarios. The integrated DEA-neural network approach provides a way to assess performance, benchmark schools, and predict future efficiency.
The document discusses managing uncertainty in supply chains through the use of safety inventory. It defines safety inventory as inventory carried to satisfy unexpected demand. The appropriate level of safety inventory is determined by the uncertainty in demand and supply as well as the desired level of product availability. Higher safety inventory improves availability but increases holding costs. The document provides formulas and examples for calculating safety inventory levels required to meet a desired cycle service level, fill rate, or both, given factors like demand uncertainty and lead time. Reducing lead time and demand uncertainty can lower the required safety inventory.
This document discusses revenue management techniques in supply chains. It begins by defining revenue management as using pricing to increase profits from limited supply chain assets like capacity and inventory. Revenue management is most effective when product value varies between customer segments, products are perishable, demand has peaks and valleys, or products are sold in bulk and on the spot market. The document then examines pricing strategies for multiple customer segments, dynamic pricing of perishable assets over time, and optimizing contracts between bulk and spot sales. Throughout, it highlights tradeoffs between committing capacity early at lower prices versus waiting for higher prices.
Future Bio Science SCM Project Report_Bharat ChaujarBharat Chaujar
This document provides an overview of a report on understanding procurement and distribution models for a company called Future Bio Science. It discusses direct and indirect procurement, types of distribution channels, and gives profiles of some of Future Bio Science's principal companies that it imports biotechnical equipment from, such as Cleaver Scientific, Techno Plastic Products, and Biocision. The objectives of the report and internship were to analyze Future Bio Science's distribution policy and processes around procurement, imports, inventory management and other supply chain functions.
HPCL has opportunities to expand its allied retail business (ARB) through strategic tie-ups. Currently, HPCL earns additional revenue through non-fuel offerings like ATMs, food counters, and convenience stores. It plans to set up more rural fuel pumps and partner with more banks and fast food brands. HPCL aims to enhance customer loyalty through programs like DriveTrack Plus and beautify fuel stations under its Club HP brand. The document discusses HPCL's organization structure and key departments responsible for planning, maintenance, finance, human resources, and safety.
The document discusses how online sales have impacted distribution network design. It provides examples of Dell and Amazon, noting both saw reduced inventory and facility costs but higher transportation costs from distributing online. It also examines Peapod, an online grocer, highlighting challenges in fulfilling grocery orders due to products' bulky nature and need for fast delivery. Overall, online sales allow flexibility but also complexity from balancing various customer service and cost factors in distribution.
This document summarizes a summer internship report on the business impact of standard operating procedures (SOPs) in retail outlet operations for urban and highway dealers. The intern conducted research at Hindustan Petroleum Corporation Limited outlets in Noida, Meerut, and Muzaffarnagar. The objectives were to understand the impact of SOPs, compare SOP-enabled and non-enabled outlets, and inspect SOP adherence. Key findings included the percentage of SOP-enabled outlets in each city and maintenance levels for five SOP components. The intern concluded SOPs increase sales, productivity, and store image, meeting customer demand better. Recommendations to improve SOP implementation were provided.
This document contains an assignment for a Supply Chain Management course. It includes 6 questions related to factors affecting transportation decisions, risk pooling, a case study about Jaguar Land Rover and supplier Gobel & Partner, MTR Foods outsourcing manufacturing, short notes on inter-company strategic scope and plant location models, and how information helps resolve supply chain trade-offs. The questions vary between 2 to 10 marks and students are advised to answer all questions, with 10-mark answers being around 400 words. Evaluation criteria are provided for each question.
Project Template Sample Kerala University MBAAnujith KR
This document is a project report submitted by a student to partial fulfillment of the requirements for a Master's degree. It examines the impact of e-procurement on purchasing indirect goods for a company. The report will include a literature review on e-procurement, data collection and analysis on the company's traditional procurement vs e-procurement, results and discussions. The objective is to understand why e-procurement has not succeeded as expected for indirect purchases and measure its cost-effectiveness for the company.
The document discusses the practical experience gained from an internship at a food company. It begins with summarizing key issues facing the food industry highlighted in the movie "Food Inc", including abuse of animals, lack of respect for farmers' rights, poor working conditions, monopolization by few companies, and weak regulatory systems. It then outlines the vision, mission, objectives, organizational structure with roles and responsibilities, salary structure, plant layout, product formulation, supplier qualification, ingredient specifications, unit operations, and sanitation practices of the company.
Indian Oil Corporation (IOC) is India's largest company by revenue and market share. It has a network of over 17,600 retail outlets across India selling petroleum products under various brands like Xtra Premium petrol and Xtra Mile diesel. IOC also sells other energy products like cooking gas (Indane), lubricants (Servo), and has launched loyalty programs like Xtra Power Fleet Card to build customer loyalty. The document provides an overview of IOC's operations, market share, brands and products.
Strategy Design and Business Model Improvement in a MSME Located in District ...M. Ali Pahmi
This study aims to formulate a design for developing a new business model strategy that is expected to improve the competitiveness of the tofu MSME in cileungsi. The methodology being used is benchmarking on both MSME industries area region & formulate improvements in the process and product lines, which are made in a new strategy map and business model, finally validated by the AVAC method.
This document provides an overview of the supply chain of Nescafe coffee in India through a study conducted by Bhaskar Kumar for their MBA degree. It discusses Nescafe's supply chain processes in India, including upstream supply chain management involving farmers and local coffee businesses. The objective of the study is to analyze Nescafe's supply chain management in India and discuss related social welfare programs, issues, and challenges regarding the coffee supply chain.
challenges in warehouse operations at pantaloons bhubaneswarAmiya Mohanty
The document discusses challenges in warehouse operations for the retail industry based on a case study of Pantaloons. It aims to identify challenges and recommend measures to improve the warehouse system. The researcher studied various warehouse transactions and processes. Key challenges identified include lack of manpower, limited warehouse space, and time constraints for staff. Some staff lacked training in replenishment procedures. The report recommends training all staff, evaluating technology and facilities to improve the distribution operations at Pantaloons Bhubaneswar.
which supply chain strategies can guarantee higher manufacturer’s operational...INFOGAIN PUBLICATION
Due to the fact that scientists and practitioners alike have interested on the leveraging manufacturing companies’ operational performance, this research examined which supply chain strategies promise manufacturers higher operational performance. Later on, we clarified whether suitable resources can play an important role in the mentioned causal relationshipsas a moderator and improve the impact of the strategies on operational performance. This study is a descriptive-exploratory research in which primary data was collected from 80 Malaysian manufacturing companies. Bivariate Correlation and Multiple Regression in SPSS was applied for analyzing data. Output showed that many suppliers, few suppliers, and keiretsu network strategies enable manufacturers to achieve satisfactory level of operational performance; but, vertical integration. More importantly, suitable resources can leverage the effect of just vertical integration strategy on operational performance.
Internship PPT - The Effectiveness of Logistics and Distribution - DTDC CouriersAvinash Heston
The document presents a project on evaluating the effectiveness of logistics, distribution, and customer satisfaction at DTDC, a leading courier service company in India. The project aims to understand DTDC's position in the market, problems in international and domestic segments, and customer satisfaction levels. It will research revenue in logistics/distribution, customer reach and reaction, and issues in distribution. The design involves interacting with employees through meetings, discussions, and questionnaires. Learning points are that logistics is an important intermediary sector, customer relations are key, and flexibility according to customer needs is important in service businesses.
Heineken uses a Product-Service System (PSS) business model that is product-oriented and focused on creating value. The company's sustainability program called "Brewing a Better World" integrates sustainability into its strategy. This includes making the supply chain more sustainable by helping suppliers, especially in Africa, become more efficient and adopt practices like new seed varieties. It also focuses on reducing resources used in brewing like water, CO2 emissions, and electricity through initiatives like its Total Productive Maintenance Program. While Heineken works to build sustainable supplier relationships, it could better communicate and market these efforts to increase visibility and trust with stakeholders.
FMCG Sector analysis, Porter five model in fmcg sector, company analysis of ITC Ltd., Business model of ITC-Ltd, Function of HR Manager, Type of Training in ITC Ltd., Performance management cycle of itc ltd. Employee benefit provided in ITC Ltd.
Customer overview of retail outlets hpcl vs. reliance Supa Buoy
Hi Friends
This is supa bouy
I am a mentor, Friend for all Management Aspirants, Any query related to anything in Management, Do write me @ supabuoy@gmail.com.
I will try to assist the best way I can.
Cheers to lyf…!!!
Supa Bouy
Competitive Analysis - Literature Review of Analytical FrameworksLanguage Explore
The PLC is not the businessman's panacea but it can be useful if used in combination with other models and frameworks and alongside good management judgement.
The BCG assumed that market share is a good indicator of cash requirement though in reality, profits and cash flow depended on a lot other things than just market share and growth.
Porter who was convinced that the BCG Matrix by itself was not very useful in determining strategy for a particular business and was too simplistic, proposed some analytical tools and techniques in his three core concepts of the Basic Competitive Forces, the Generic Competitive Strategies and the Value Chain.
The document provides an overview of Samsung's history and operations in India. It details Samsung's entry into the Indian market in 1995 and its subsequent expansion, including establishing manufacturing facilities and R&D centers. It also outlines Samsung's product portfolio, core values and vision, and some of its key achievements in India such as becoming the largest mobile brand and a leader in product categories like LED TVs and refrigerators.
This document discusses using data envelopment analysis (DEA) and neural networks to model the performance of business schools in India. DEA was used to evaluate the efficiency of 49 Indian business schools based on their inputs and outputs. The average efficiency score was 0.625 using the CCR model and 0.888 using the BCC model. Neural networks were then used to predict efficiency scores when inputs change, allowing schools to generate "what if" scenarios. The integrated DEA-neural network approach provides a way to assess performance, benchmark schools, and predict future efficiency.
The document discusses managing uncertainty in supply chains through the use of safety inventory. It defines safety inventory as inventory carried to satisfy unexpected demand. The appropriate level of safety inventory is determined by the uncertainty in demand and supply as well as the desired level of product availability. Higher safety inventory improves availability but increases holding costs. The document provides formulas and examples for calculating safety inventory levels required to meet a desired cycle service level, fill rate, or both, given factors like demand uncertainty and lead time. Reducing lead time and demand uncertainty can lower the required safety inventory.
This document discusses revenue management techniques in supply chains. It begins by defining revenue management as using pricing to increase profits from limited supply chain assets like capacity and inventory. Revenue management is most effective when product value varies between customer segments, products are perishable, demand has peaks and valleys, or products are sold in bulk and on the spot market. The document then examines pricing strategies for multiple customer segments, dynamic pricing of perishable assets over time, and optimizing contracts between bulk and spot sales. Throughout, it highlights tradeoffs between committing capacity early at lower prices versus waiting for higher prices.
Future Bio Science SCM Project Report_Bharat ChaujarBharat Chaujar
This document provides an overview of a report on understanding procurement and distribution models for a company called Future Bio Science. It discusses direct and indirect procurement, types of distribution channels, and gives profiles of some of Future Bio Science's principal companies that it imports biotechnical equipment from, such as Cleaver Scientific, Techno Plastic Products, and Biocision. The objectives of the report and internship were to analyze Future Bio Science's distribution policy and processes around procurement, imports, inventory management and other supply chain functions.
HPCL has opportunities to expand its allied retail business (ARB) through strategic tie-ups. Currently, HPCL earns additional revenue through non-fuel offerings like ATMs, food counters, and convenience stores. It plans to set up more rural fuel pumps and partner with more banks and fast food brands. HPCL aims to enhance customer loyalty through programs like DriveTrack Plus and beautify fuel stations under its Club HP brand. The document discusses HPCL's organization structure and key departments responsible for planning, maintenance, finance, human resources, and safety.
The document discusses how online sales have impacted distribution network design. It provides examples of Dell and Amazon, noting both saw reduced inventory and facility costs but higher transportation costs from distributing online. It also examines Peapod, an online grocer, highlighting challenges in fulfilling grocery orders due to products' bulky nature and need for fast delivery. Overall, online sales allow flexibility but also complexity from balancing various customer service and cost factors in distribution.
This document summarizes a summer internship report on the business impact of standard operating procedures (SOPs) in retail outlet operations for urban and highway dealers. The intern conducted research at Hindustan Petroleum Corporation Limited outlets in Noida, Meerut, and Muzaffarnagar. The objectives were to understand the impact of SOPs, compare SOP-enabled and non-enabled outlets, and inspect SOP adherence. Key findings included the percentage of SOP-enabled outlets in each city and maintenance levels for five SOP components. The intern concluded SOPs increase sales, productivity, and store image, meeting customer demand better. Recommendations to improve SOP implementation were provided.
This document contains an assignment for a Supply Chain Management course. It includes 6 questions related to factors affecting transportation decisions, risk pooling, a case study about Jaguar Land Rover and supplier Gobel & Partner, MTR Foods outsourcing manufacturing, short notes on inter-company strategic scope and plant location models, and how information helps resolve supply chain trade-offs. The questions vary between 2 to 10 marks and students are advised to answer all questions, with 10-mark answers being around 400 words. Evaluation criteria are provided for each question.
Project Template Sample Kerala University MBAAnujith KR
This document is a project report submitted by a student to partial fulfillment of the requirements for a Master's degree. It examines the impact of e-procurement on purchasing indirect goods for a company. The report will include a literature review on e-procurement, data collection and analysis on the company's traditional procurement vs e-procurement, results and discussions. The objective is to understand why e-procurement has not succeeded as expected for indirect purchases and measure its cost-effectiveness for the company.
The document discusses the practical experience gained from an internship at a food company. It begins with summarizing key issues facing the food industry highlighted in the movie "Food Inc", including abuse of animals, lack of respect for farmers' rights, poor working conditions, monopolization by few companies, and weak regulatory systems. It then outlines the vision, mission, objectives, organizational structure with roles and responsibilities, salary structure, plant layout, product formulation, supplier qualification, ingredient specifications, unit operations, and sanitation practices of the company.
Indian Oil Corporation (IOC) is India's largest company by revenue and market share. It has a network of over 17,600 retail outlets across India selling petroleum products under various brands like Xtra Premium petrol and Xtra Mile diesel. IOC also sells other energy products like cooking gas (Indane), lubricants (Servo), and has launched loyalty programs like Xtra Power Fleet Card to build customer loyalty. The document provides an overview of IOC's operations, market share, brands and products.
Strategy Design and Business Model Improvement in a MSME Located in District ...M. Ali Pahmi
This study aims to formulate a design for developing a new business model strategy that is expected to improve the competitiveness of the tofu MSME in cileungsi. The methodology being used is benchmarking on both MSME industries area region & formulate improvements in the process and product lines, which are made in a new strategy map and business model, finally validated by the AVAC method.
This document provides an overview of the supply chain of Nescafe coffee in India through a study conducted by Bhaskar Kumar for their MBA degree. It discusses Nescafe's supply chain processes in India, including upstream supply chain management involving farmers and local coffee businesses. The objective of the study is to analyze Nescafe's supply chain management in India and discuss related social welfare programs, issues, and challenges regarding the coffee supply chain.
challenges in warehouse operations at pantaloons bhubaneswarAmiya Mohanty
The document discusses challenges in warehouse operations for the retail industry based on a case study of Pantaloons. It aims to identify challenges and recommend measures to improve the warehouse system. The researcher studied various warehouse transactions and processes. Key challenges identified include lack of manpower, limited warehouse space, and time constraints for staff. Some staff lacked training in replenishment procedures. The report recommends training all staff, evaluating technology and facilities to improve the distribution operations at Pantaloons Bhubaneswar.
Transportation Model Application and Performance of Seven up.pdflalitsamal1
This document summarizes a research study on the relationship between transportation modeling and performance of Seven Up Bottling Company in Nigeria. The study used a survey design and interview method to collect data, which was analyzed using Tora software. Key findings include:
1) There is a relationship between the distribution routes and distribution costs of Seven Up Bottling Company.
2) Transportation modeling revealed an optimal total distribution cost of 6,800,000 Naira and allocation of products from plants to depots along the lowest possible cost route.
3) Applying transportation modeling can help associate distribution routes with company performance by reducing distribution costs.
This study examines the influence of enterprise resource planning (ERP) systems on inventory management in private primary schools in Kenya, using Bridge International Academies as a case study. The study found that cost management, supplier relationships, customer service, and employee productivity were positively influenced by ERP systems. It recommends that schools properly manage inventory costs and payments, form beneficial supplier relationships, continuously monitor performance to ensure customer satisfaction, and utilize ERP systems to increase efficiency and productivity. The goal of the research was to evaluate how ERP systems impact key aspects of inventory management in private primary schools.
This paper deals with the applications of optimization principle in optimizing
profits of a production industry using linear programming to examine the production
cost and determine its optimal profit. Linear programming is an operation research
technique which is widely used in finding solutions to managerial decision problems.
However, many enterprises make more use of the trial-and-error method. As such,
firms have been finding it difficult in allocating scarce resources in a manner that will
ensure profit maximization and/or cost minimization.
This paper makse use of secondary data collected from the records of the
Landmark University Bakery on five types of bread produced in the firm which
include Family loaf, sliced family bread, Chocolate loaf, medium size bread, small
size bread. A problem of this nature was identified as a linear programming problem,
formulated in Mathematical terms and solved using AMPL software. The solution
obtained revealed that Landmark bakery unit should concentrate much more in
production of 14,000 loaves of Family loaf and 10,571 loaves of Chocolate bread
while others type should be less produced since their value is turning to zero in order
to achieve a maximum monthly profit of N1,860,000. From the analysis, it was
observed that Family loaf and the Chocolate bread contributed objectively to the
profit. Hence, more of Family loaf and Chocolate bread are needed to be produced
and sold in order to maximize the profit
Importance of Production Planning and Control in Small Manufacturing Enterprisesinventionjournals
SMEs are growing nowadays. The companies are dependent on SMEs. SMEs are acting as vendor for them. For fulfilling the order of the big companies the SMEs have to deliver the product within schedule time. This has compelled the SMEs to look into the production planning and control of the unit. If the SMEs properly apply the PPC, the production system is going to be fastened and tries to focus over that of the SMEs by taking pragmatic approach in that regard.
This document evaluates different supply chain strategies for apparel manufacturing organizations using the Analytical Hierarchy Process (AHP). It first describes lean, agile and leagile supply chain strategies. It then outlines the AHP methodology and applies it to determine the most suitable strategy. Key evaluation factors are identified and weighted based on pairwise comparisons. Sub-factors are also identified and weighted for each key factor. The performance of lean, agile and leagile strategies are rated for each sub-factor. Overall scores are calculated to validate that leagile supply chain is the best strategy for the case study apparel organization.
The role of manufacturing operations is the process of beginning a production process to a task of final assem-bly, with increased reliance on a significant number of supply chain participants who have differing objectives, perspectives and processes. However, an effective partnering between companies and their suppliers remains a key to lean supply chain management excel-lence. A lean supply chain offers competitive advantage to the suppliers, therefore the need for the Nigerian mar-ket to embrace the idea of lean based supply chain system. This paper examines the prospects of transforming from the traditional supply chain system to a lean supply chain system in Nigeria. But it is noted that the process could be tasking. It was observed that to succeed in lean supply chain management, organizations must be willing to share risks and rewards, and to build the underlying infrastructure to apply these tools. In this paper it was resounded that the rewards could be in-flaming as various benefits such as a stronger costumer, supplier relationship, increased competitive advantage with velocity of supply etc, applies. It is concluded that, to the Nigerian economy it will be increased cash flow from the costumers and increased market forces.
MBA Project report on Just In Time Management - Final Report
This report provides an analysis and evaluation of the Just-In-Time system, the advantages and disadvantages of the system and how it would benefit AG & Z. The Just-In-Time (JIT) system is a process where goods are ordered as required, as opposed to the currently used batch processing system where goods are made in bulk and stored in warehouses until sold. The Just-In-Time system was initially developed to not only cut down the amount of waste produced by other systems, which was seen as incurring unnecessary costs rather than adding value to the company, but to also meet customer demands with minimum delays. It has been found that when implemented correctly the JIT system can benefit the company in numerous ways.
International Journal of Business and Management Invention (IJBMI) is an international journal intended for professionals and researchers in all fields of Business and Management. IJBMI publishes research articles and reviews within the whole field Business and Management, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
The document outlines a thesis proposal on designing a supply chain for MEAD Food Complex Company to minimize costs. The objectives are to evaluate the company's current supply chain strategy, assess supplier locations and numbers, determine optimal transportation methods, and design an optimal distribution system. A literature review identified challenges in supply chain design and coordination across organizations. The methodology will use a multi-criteria decision-making approach with data collection from company reports and site visits to model and analyze the supply chain network. The results aim to provide a new optimal supply chain design to reduce MEAD's costs and improve customer satisfaction.
Each company establishes a mission and strategies to achieve their goals. A mission statement outlines the company's objectives and focuses processes. Strategies are then developed across four levels - strategic, structural, functional, and implementation. When creating a logistics strategy, companies evaluate areas like transportation, outsourcing, logistics systems, competitors, and information to define service levels and costs. Companies also adopt global operations strategies like international, multidomestic, global, and transnational based on balancing responsiveness in local markets with cost reductions.
This document presents a case study on the logistics performance of Kian Joo Can Factory Berhad (KJCF), a Malaysian manufacturing company. The study examines KJCF's supply chain operations, which involve procuring raw materials from suppliers and transporting them to multiple manufacturing plants located across several Malaysian states and in Vietnam. The plants then distribute finished aluminum cans to customers both domestically and abroad. The study analyzes KJCF's current supply chain performance using both qualitative measures like quality certifications as well as quantitative measures from financial and management data to identify areas for improvement.
The document discusses the Kaizen Costing System (KCS) and its potential to provide managers with strategies for reducing production costs at different stages of a product's life cycle. KCS involves continuous, incremental improvements to manufacturing processes. It was developed by Japanese firms as an alternative to traditional costing systems that focuses on non-quantifiable factors like quality and flexibility. The study examines accountants' perceptions of whether implementing KCS would lower costs in a product's introductory, minimal batch production, and maximum batch production phases through surveys. Statistical tests were used to analyze the data and determine if relationships exist between cost reduction strategies in the different phases.
This document discusses using mathematical programming to optimize production planning and maximize profit for textile industries in Ethiopia. It presents a linear programming model and queue model to determine the optimal product mix and allocation of resources. The models aim to satisfy customer orders while maximizing total profit. Data was collected from 49 textile companies and used to estimate model parameters. The results showed the company's total monthly profit could be increased by 49.3% (from 4.4 million Birr to 9.3 million Birr) by applying the linear programming and queue models to production planning and resource allocation.
The document is an internship report submitted by Nitin Sharma for his MBA program. It details his internship at the Central Warehousing Corporation Inland Container Depot in Patparganj, where he studied logistics and warehousing. The report includes an executive summary of his findings, the company profile of Central Warehousing Corporation, and sections on the objectives, scope and details of his project analyzing the marketing, operations, finance, management information systems, and record keeping of the facility.
A REVIEW ON THE STRATEGIC USE OF IT APPLICATIONS IN ACHIEVING AND SUSTAINING ...ijmpict
This document reviews how companies can use information technology applications to gain competitive advantages. It discusses several ways that IT can be strategically utilized, including using IT to innovate products and services, lower costs strategically, promote growth, achieve strategic differentiation, develop alliances to cut costs, and lock in customers. It provides examples of companies that have successfully used various IT applications like customer relationship management systems, supply chain management systems, and mobile applications to gain competitive advantages over their competitors in areas like customer service, cost reduction, and market growth.
LOGISTICS AND SUPPLY CHAIN CHALLENGES FOR THE FUTUREAshish Hande
This chapter discusses strategic planning for logistics and supply chain management. It covers the evolution of strategic planning from investment planning in the 1950s to a focus on competitive advantage today. The chapter also outlines different types of strategies such as time-based strategies focused on reducing cycle times, asset productivity strategies aimed at better utilizing inventory and facilities, technology-based strategies using disruptive technologies, and relationship-based strategies like collaboration and value nets. Finally, it discusses future trends in logistics including a shift to virtual integration and the importance of collaboration, technology, and a comprehensive supply chain perspective.
Ritesh Arya has over 15 years of experience in inventory planning, customer order fulfillment, sourcing, and program/IT system implementation. He is currently the Senior In Stock Manager at Cloudtail India Pvt Ltd, where he drives efficient use of capital through inventory management and optimizing key metrics. Prior to this, he held roles like Senior Category Manager and Senior In Stock Manager at Amazon India, and Business Supply Chain Analyst at 3M India Ltd, where he improved inventory turns, product availability, and on-time order fulfillment. He has expertise in areas like demand planning, supply chain management, and process improvement tools.
Current Ms word generated power point presentation covers major details about the micronuclei test. It's significance and assays to conduct it. It is used to detect the micronuclei formation inside the cells of nearly every multicellular organism. It's formation takes place during chromosomal sepration at metaphase.
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
Nucleophilic Addition of carbonyl compounds.pptxSSR02
Nucleophilic addition is the most important reaction of carbonyls. Not just aldehydes and ketones, but also carboxylic acid derivatives in general.
Carbonyls undergo addition reactions with a large range of nucleophiles.
Comparing the relative basicity of the nucleophile and the product is extremely helpful in determining how reversible the addition reaction is. Reactions with Grignards and hydrides are irreversible. Reactions with weak bases like halides and carboxylates generally don’t happen.
Electronic effects (inductive effects, electron donation) have a large impact on reactivity.
Large groups adjacent to the carbonyl will slow the rate of reaction.
Neutral nucleophiles can also add to carbonyls, although their additions are generally slower and more reversible. Acid catalysis is sometimes employed to increase the rate of addition.
The use of Nauplii and metanauplii artemia in aquaculture (brine shrimp).pptxMAGOTI ERNEST
Although Artemia has been known to man for centuries, its use as a food for the culture of larval organisms apparently began only in the 1930s, when several investigators found that it made an excellent food for newly hatched fish larvae (Litvinenko et al., 2023). As aquaculture developed in the 1960s and ‘70s, the use of Artemia also became more widespread, due both to its convenience and to its nutritional value for larval organisms (Arenas-Pardo et al., 2024). The fact that Artemia dormant cysts can be stored for long periods in cans, and then used as an off-the-shelf food requiring only 24 h of incubation makes them the most convenient, least labor-intensive, live food available for aquaculture (Sorgeloos & Roubach, 2021). The nutritional value of Artemia, especially for marine organisms, is not constant, but varies both geographically and temporally. During the last decade, however, both the causes of Artemia nutritional variability and methods to improve poorquality Artemia have been identified (Loufi et al., 2024).
Brine shrimp (Artemia spp.) are used in marine aquaculture worldwide. Annually, more than 2,000 metric tons of dry cysts are used for cultivation of fish, crustacean, and shellfish larva. Brine shrimp are important to aquaculture because newly hatched brine shrimp nauplii (larvae) provide a food source for many fish fry (Mozanzadeh et al., 2021). Culture and harvesting of brine shrimp eggs represents another aspect of the aquaculture industry. Nauplii and metanauplii of Artemia, commonly known as brine shrimp, play a crucial role in aquaculture due to their nutritional value and suitability as live feed for many aquatic species, particularly in larval stages (Sorgeloos & Roubach, 2021).
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
The binding of cosmological structures by massless topological defectsSérgio Sacani
Assuming spherical symmetry and weak field, it is shown that if one solves the Poisson equation or the Einstein field
equations sourced by a topological defect, i.e. a singularity of a very specific form, the result is a localized gravitational
field capable of driving flat rotation (i.e. Keplerian circular orbits at a constant speed for all radii) of test masses on a thin
spherical shell without any underlying mass. Moreover, a large-scale structure which exploits this solution by assembling
concentrically a number of such topological defects can establish a flat stellar or galactic rotation curve, and can also deflect
light in the same manner as an equipotential (isothermal) sphere. Thus, the need for dark matter or modified gravity theory is
mitigated, at least in part.
When I was asked to give a companion lecture in support of ‘The Philosophy of Science’ (https://shorturl.at/4pUXz) I decided not to walk through the detail of the many methodologies in order of use. Instead, I chose to employ a long standing, and ongoing, scientific development as an exemplar. And so, I chose the ever evolving story of Thermodynamics as a scientific investigation at its best.
Conducted over a period of >200 years, Thermodynamics R&D, and application, benefitted from the highest levels of professionalism, collaboration, and technical thoroughness. New layers of application, methodology, and practice were made possible by the progressive advance of technology. In turn, this has seen measurement and modelling accuracy continually improved at a micro and macro level.
Perhaps most importantly, Thermodynamics rapidly became a primary tool in the advance of applied science/engineering/technology, spanning micro-tech, to aerospace and cosmology. I can think of no better a story to illustrate the breadth of scientific methodologies and applications at their best.
Or: Beyond linear.
Abstract: Equivariant neural networks are neural networks that incorporate symmetries. The nonlinear activation functions in these networks result in interesting nonlinear equivariant maps between simple representations, and motivate the key player of this talk: piecewise linear representation theory.
Disclaimer: No one is perfect, so please mind that there might be mistakes and typos.
dtubbenhauer@gmail.com
Corrected slides: dtubbenhauer.com/talks.html
ESR spectroscopy in liquid food and beverages.pptxPRIYANKA PATEL
With increasing population, people need to rely on packaged food stuffs. Packaging of food materials requires the preservation of food. There are various methods for the treatment of food to preserve them and irradiation treatment of food is one of them. It is the most common and the most harmless method for the food preservation as it does not alter the necessary micronutrients of food materials. Although irradiated food doesn’t cause any harm to the human health but still the quality assessment of food is required to provide consumers with necessary information about the food. ESR spectroscopy is the most sophisticated way to investigate the quality of the food and the free radicals induced during the processing of the food. ESR spin trapping technique is useful for the detection of highly unstable radicals in the food. The antioxidant capability of liquid food and beverages in mainly performed by spin trapping technique.
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...University of Maribor
Slides from talk:
Aleš Zamuda: Remote Sensing and Computational, Evolutionary, Supercomputing, and Intelligent Systems.
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Inter-Society Networking Panel GRSS/MTT-S/CIS Panel Session: Promoting Connection and Cooperation
https://www.etran.rs/2024/en/home-english/
ANAMOLOUS SECONDARY GROWTH IN DICOT ROOTS.pptxRASHMI M G
Abnormal or anomalous secondary growth in plants. It defines secondary growth as an increase in plant girth due to vascular cambium or cork cambium. Anomalous secondary growth does not follow the normal pattern of a single vascular cambium producing xylem internally and phloem externally.
2. J. Open Innov. Technol. Mark. Complex.2021, 7, x FOR PEER REVIEW 2 of 20
Central Kitchen (CK) used to store raw materials from suppliers and would be distri-
buted to each outlet. The business process in PT XYZ is every night, each outlet sends a
purchase order to CK, and on the next day they will send an employee to picks the raw
materials up from the CK.
The problem that PT XYZ have is inefficiency in the current distribution method. It
contributes to the high distribution cost that the company should spend because each
outlet conducts two to ten times of trip every day. Thus, PT XYZ wants to change the
distribution method from each outlet to pick the raw materials from the CK (operator
pickup) into the direct delivery method from CK to each outlet (direct shipping).
By implementing the new distribution method, PT XYZ have to buy operational
vehicles to distribute raw materials from the CK to each outlet. The new distribution
method design will be influenced by operational vehicles’ efficiency, where they can
distribute raw materials with minimal cost. Hence, PT XYZ needs to determine the most
appropriate distribution route to minimize transportation costs expensed.
In conducting the optimum route determination strategy in PT XYZ, a model for
finding the most appropriate solution is needed. Vehicle Routing Problem (VRP) is the
most appropriate model to use for problems related to route determination. VRP model
can be defined as finding the optimal route from a depot to several customers in scattered
areas and with different demand numbers. The VRP Model has several variations, which
are grouped based on the limitations they have. The most appropriate completion model
for the problem in PT XYZ where CK and outlets have their service time in delivery and
receiving was the Vehicle Routing Problem with Time Windows (VRPTW).
VRPTW model is used to schedule trips from a group of vehicles with limited ca-
pacity and travel time from the main depot to all customers in different locations, with
demand and service time in particular (Nugraha and Mahmudy, 2015). Penentlitian se-
belumnya terkait VRPTW for restaurant chain.
Theoretically, VRPTW is an NP-hard problem, where solving the problem requires
complex computational effort and long computation time [2]. So, one method that can be
used to solve the NP-hard problem by using the metaheuristic method. The metaheuris-
tic method was created to solve high-complexity problems and generate a near-optimum
solution [2].
Solving optimization problem using metaheuristic algorithms tend to increase every
year. One of the recent metaheuristic methods that many researchers developed is Sym-
biotic Organisms Search (SOS) algorithm. Another metaheuristic algorithm commonly
used to solve determination optimization problems is Particle Swarm Optimization
(PSO). SOS and PSO have the same solution-seeking characteristics inspired by natural
principles of living things and population-based approaches. Due to the same characte-
ristics of SOS and PSO algorithms, many researchers evaluated and tested the solution
quality generated from both algorithms.
The comparison of performance evaluation between SOS and PSO algorithms was
conducted by Yu et al. [3], which applied SOS and PSO algorithms on the CVRP problem.
There was also research by Umam et al. [4] that modified the SOS algorithm for the TSP
problem and compared the generated solution quality with the solution obtained from
the PSO algorithm. Another research that tested both algorithms’ performance is by Pa-
rayogo et al. [5] in their research regarding the layout determination of construction
project facility based on working mileage.
This research aimed to conduct performance quality testing between SOS and PSO
algorithms in solving the VRPTW problem based on the research background. The algo-
rithm with the best solution performance will be implemented in the company’s route
determination. Besides, this research also conducted a feasibility analysis using the
capital budgeting method to discover the feasibility of the new distribution method plan
to be implemented in the company’s system.
2. Deskripsi Permasalahan
3. J. Open Innov. Technol. Mark. Complex.2021, 7, x FOR PEER REVIEW
Metode pendistribusian bahan makanan dari Central Kitchen (CK) ke ma
ing-masing outlet di PT XYZ yang kurang optimal menjadi sebuah permasalahan yang
perlu diperbaiki. Permasalahan inefisiensi dalam metode pendistribusian di PT XYZ
menyebabkan tingginya biaya distribusi yang perlu dikeluarkan. Hal ini dikarenakan
dalam pengam
melakukan dua sampai sepuluh kali perjalanan setiap harinya. Selain itu,terjadinya k
terlambatan dalam pengambilan bahan makanan oleh pegawai dari masing
outlet membuat kurang opti
Permasalahan lain terkait metode distribusi yang saat ini diterapkan oleh PT XYZ
yaitu ketidaksesuaian data barang yang ada dalam sistem inventory dengan barang yang
disimpan. Hal ini terjadi dikarenakan, pe
melebihi waktu pelayanan CK.
han-permasalahan terkait sistem pendistribusian yang kurang optimal, PT XYZ ingin
menerapakan sebuah kebijakan baru. Dimana kebijakan baru t
pengiriman bahan makanan yang diambil oleh karyawan masing
tor pickup) menjadi CK yang mengirimkan secara langsung bahan makanan ke ma
ing-masing outlet (direct shipping). Dengan kebijakan yang baru tersebut, PT
membeli kendaraan operasional perusahaan yang digunakan untuk mendistribusikan
bahan makanan dari CK ke masing
, x FOR PEER REVIEW
Metode pendistribusian bahan makanan dari Central Kitchen (CK) ke ma
masing outlet di PT XYZ yang kurang optimal menjadi sebuah permasalahan yang
perlu diperbaiki. Permasalahan inefisiensi dalam metode pendistribusian di PT XYZ
menyebabkan tingginya biaya distribusi yang perlu dikeluarkan. Hal ini dikarenakan
dalam pengambilan bahan makanan dari CK ke masing-masing outlet, kendaraan harus
melakukan dua sampai sepuluh kali perjalanan setiap harinya. Selain itu,terjadinya k
terlambatan dalam pengambilan bahan makanan oleh pegawai dari masing
outlet membuat kurang optimalnya waktu pegawai dalam bekerja satu harinya.
Permasalahan lain terkait metode distribusi yang saat ini diterapkan oleh PT XYZ
ketidaksesuaian data barang yang ada dalam sistem inventory dengan barang yang
disimpan. Hal ini terjadi dikarenakan, pegawai dari masing-masing outlet datang ke CK
melebihi waktu pelayanan CK. Oleh karena itu, untuk mengatasi permasal
permasalahan terkait sistem pendistribusian yang kurang optimal, PT XYZ ingin
menerapakan sebuah kebijakan baru. Dimana kebijakan baru tersebut mengganti metode
pengiriman bahan makanan yang diambil oleh karyawan masing
tor pickup) menjadi CK yang mengirimkan secara langsung bahan makanan ke ma
masing outlet (direct shipping). Dengan kebijakan yang baru tersebut, PT
membeli kendaraan operasional perusahaan yang digunakan untuk mendistribusikan
bahan makanan dari CK ke masing-masing outlet.
Illustrate Old Distribution Method
3 of 20
Metode pendistribusian bahan makanan dari Central Kitchen (CK) ke mas-
masing outlet di PT XYZ yang kurang optimal menjadi sebuah permasalahan yang
perlu diperbaiki. Permasalahan inefisiensi dalam metode pendistribusian di PT XYZ
menyebabkan tingginya biaya distribusi yang perlu dikeluarkan. Hal ini dikarenakan
masing outlet, kendaraan harus
melakukan dua sampai sepuluh kali perjalanan setiap harinya. Selain itu,terjadinya ke-
terlambatan dalam pengambilan bahan makanan oleh pegawai dari masing-masing
malnya waktu pegawai dalam bekerja satu harinya.
Permasalahan lain terkait metode distribusi yang saat ini diterapkan oleh PT XYZ
ketidaksesuaian data barang yang ada dalam sistem inventory dengan barang yang
masing outlet datang ke CK
Oleh karena itu, untuk mengatasi permasala-
permasalahan terkait sistem pendistribusian yang kurang optimal, PT XYZ ingin
ersebut mengganti metode
pengiriman bahan makanan yang diambil oleh karyawan masing-masing outlet (opera-
tor pickup) menjadi CK yang mengirimkan secara langsung bahan makanan ke mas-
masing outlet (direct shipping). Dengan kebijakan yang baru tersebut, PT XYZ ingin
membeli kendaraan operasional perusahaan yang digunakan untuk mendistribusikan
4. J. Open Innov. Technol. Mark. Complex.2021, 7, x FOR PEER REVIEW
Dalam melakukan pembelian kendaraan
makanan, PT XYZ memiliki beberapa faktor pertimbangan dalam memilih moda
trasnsportasi yang paling tepat untuk diterapkan dalam operasional perusahaan. Faktor
pertama yaitu total biaya investasi, perusahaan menetap
vestasi yang dikeluarkan tidak lebih dari Rp 120.000.000. Faktor kedua yaitu fleksibilitas
operasional kendaraan, perusahaan menginginkan moda trasnsportasi yang dapat be
gerak dengan cepat dan dapat menyesuaikan dengan berbagai
memiliki biaya bahan bakar yang rendah. Faktor yang terakhir yaitu penggunaan lahan
parkir karena tidak semua outlet memiliki lahan parkir untuk kendaraan yang luas, s
hingga hal ini yang menjadi salah satu faktor pertimbangan dala
transportasi.
Berdasarkan faktor
transportasi yang tepat untuk digunakan yaitu kendaraan roda dua dengan box peng
riman berkapasitas 50kg dan kendaraan roda tiga berkapasitas 250kg. Ba
kendaraan yang nantinya digunakan juga mengikuti besarnya permintaan dari ma
ing-masing outlet untuk tujuh hari pengiriman. Dimana besarnya permintaan outlet
untuk tujuh hari pengiriman yaitu 207kg sampai dengan 295kg. Sehingga jumlah ke
daraan yang akan dibeli untuk memenuhi permintaan semua outlet yaitu sebanyak
enam kendaraan motor roda dua dan dua kendaraan motor roda tiga.
Untuk meminimumkan biaya trannportasi yang nantinya dikeluarkan oleh PT XYZ,
pada penelitian ini akan dilakukan den
kan pendistribusian bahan makanan. Pencarian rute yang optimal nantinya akan
menggunakan model Vehicle Routing Problem with Time Windows (VRPTW) dengan
metode metaheuristik yaitu algoritma SOS dan PSO sebagai met
Setalah mengetahui rute serta biaya transportasi yang paling optimal, penelitian ini juga
akan membahas terkait analisis kelayakan investasi dari kendaraan operasional yang
akan dibeli.
Berdasarkan penjelasan di atas, untuk dapat menera
yang baru di PT XYZ, maka dibuat dua skenario pengiriman bahan makanan dengan j
nis kenadaraan yang berbeda.
1. Skenario Pengiriman Pertama
, x FOR PEER REVIEW
Illustrate New Distribution Method
Dalam melakukan pembelian kendaraan operasional untuk mendistribusikan bahan
makanan, PT XYZ memiliki beberapa faktor pertimbangan dalam memilih moda
trasnsportasi yang paling tepat untuk diterapkan dalam operasional perusahaan. Faktor
pertama yaitu total biaya investasi, perusahaan menetapkan bahwa besarnya biaya i
vestasi yang dikeluarkan tidak lebih dari Rp 120.000.000. Faktor kedua yaitu fleksibilitas
operasional kendaraan, perusahaan menginginkan moda trasnsportasi yang dapat be
gerak dengan cepat dan dapat menyesuaikan dengan berbagai kondisi pengiriman serta
memiliki biaya bahan bakar yang rendah. Faktor yang terakhir yaitu penggunaan lahan
parkir karena tidak semua outlet memiliki lahan parkir untuk kendaraan yang luas, s
hingga hal ini yang menjadi salah satu faktor pertimbangan dala
Berdasarkan faktor-faktor yang dipertimbangkan oleh perusahaan, maka moda
transportasi yang tepat untuk digunakan yaitu kendaraan roda dua dengan box peng
riman berkapasitas 50kg dan kendaraan roda tiga berkapasitas 250kg. Ba
kendaraan yang nantinya digunakan juga mengikuti besarnya permintaan dari ma
masing outlet untuk tujuh hari pengiriman. Dimana besarnya permintaan outlet
untuk tujuh hari pengiriman yaitu 207kg sampai dengan 295kg. Sehingga jumlah ke
aan yang akan dibeli untuk memenuhi permintaan semua outlet yaitu sebanyak
enam kendaraan motor roda dua dan dua kendaraan motor roda tiga.
Untuk meminimumkan biaya trannportasi yang nantinya dikeluarkan oleh PT XYZ,
pada penelitian ini akan dilakukan dengan pencarian rute yang optimal untuk melak
kan pendistribusian bahan makanan. Pencarian rute yang optimal nantinya akan
menggunakan model Vehicle Routing Problem with Time Windows (VRPTW) dengan
metode metaheuristik yaitu algoritma SOS dan PSO sebagai met
Setalah mengetahui rute serta biaya transportasi yang paling optimal, penelitian ini juga
akan membahas terkait analisis kelayakan investasi dari kendaraan operasional yang
Berdasarkan penjelasan di atas, untuk dapat menerapkan kebijakan pendistribusian
yang baru di PT XYZ, maka dibuat dua skenario pengiriman bahan makanan dengan j
nis kenadaraan yang berbeda.
Skenario Pengiriman Pertama
4 of 20
operasional untuk mendistribusikan bahan
makanan, PT XYZ memiliki beberapa faktor pertimbangan dalam memilih moda
trasnsportasi yang paling tepat untuk diterapkan dalam operasional perusahaan. Faktor
kan bahwa besarnya biaya in-
vestasi yang dikeluarkan tidak lebih dari Rp 120.000.000. Faktor kedua yaitu fleksibilitas
operasional kendaraan, perusahaan menginginkan moda trasnsportasi yang dapat ber-
kondisi pengiriman serta
memiliki biaya bahan bakar yang rendah. Faktor yang terakhir yaitu penggunaan lahan
parkir karena tidak semua outlet memiliki lahan parkir untuk kendaraan yang luas, se-
hingga hal ini yang menjadi salah satu faktor pertimbangan dalam pemilihan moda
faktor yang dipertimbangkan oleh perusahaan, maka moda
transportasi yang tepat untuk digunakan yaitu kendaraan roda dua dengan box pengi-
riman berkapasitas 50kg dan kendaraan roda tiga berkapasitas 250kg. Banyaknya jumlah
kendaraan yang nantinya digunakan juga mengikuti besarnya permintaan dari mas-
masing outlet untuk tujuh hari pengiriman. Dimana besarnya permintaan outlet
untuk tujuh hari pengiriman yaitu 207kg sampai dengan 295kg. Sehingga jumlah ken-
aan yang akan dibeli untuk memenuhi permintaan semua outlet yaitu sebanyak
enam kendaraan motor roda dua dan dua kendaraan motor roda tiga.
Untuk meminimumkan biaya trannportasi yang nantinya dikeluarkan oleh PT XYZ,
gan pencarian rute yang optimal untuk melaku-
kan pendistribusian bahan makanan. Pencarian rute yang optimal nantinya akan
menggunakan model Vehicle Routing Problem with Time Windows (VRPTW) dengan
metode metaheuristik yaitu algoritma SOS dan PSO sebagai metode pendekatannya.
Setalah mengetahui rute serta biaya transportasi yang paling optimal, penelitian ini juga
akan membahas terkait analisis kelayakan investasi dari kendaraan operasional yang
pkan kebijakan pendistribusian
yang baru di PT XYZ, maka dibuat dua skenario pengiriman bahan makanan dengan je-
5. J. Open Innov. Technol. Mark. Complex.2021, 7, x FOR PEER REVIEW 5 of 20
Pada skenario pertama, pengiriman dilakukan dengan menggunakan kendaraan
roda dua yaitu motor dengan tambahan tas box pengiriman sebagai media angkutnya.
Skenario pengiriman pertama memiliki frekuensi pengiriman sebanyak enam kali dalam
satu harinya. Jadwal pengiriman ini terbagi menjadi pengiriman pagi 1, pengiriman pagi
2, pengiriman siang 1, pengiriman siang 2, pengiriman sore 1, dan pengiriman sore 2.
Data yang digunakan dalam skenario pengiriman pertama yaitu merupakan data large
instance 50kg. Dimana pada data large instance 50kg, permintaan bahan makanan yang
perlu dikirimkan oleh Central Kitchen ke masing-masing outlet akan dipecah berdasar-
kan waktu pengirimannya. Hal ini dilakukan karena dalam CK sendiri, tidak semua
bahan makanan dapat dipersiapkan pada pengiriman pertama. Sehingga apabila pengi-
riman ke masing-masing outlet menunggu bahan makanan yang belum dipersiapkan,
maka yang terjadi adalah terjadinya kekurangan bahan makanan lainnya yang dibu-
tuhkan oleh masing-masing outlet. Oleh karena itulah dibuat sebuah jadwal pengiriman
bahan makanan menjadi enam kali dalam seharinya agar bahan-bahan makanan yang
tidak dapat dikirimkan pada pengiriman awal, dapat dikirimkan pada pengiriman se-
lanjutnya.
2. Skenario Pengiriman Kedua
Pada skenario kedua, pengiriman dilakukan dengan menggunakan kendaraan
motor roda tiga dengan kapasitas angkut sebesar 250kg. Data yang digunakan dalam
skenario pengiriman kedua yaitu data large instance 250kg. Skenario pengiriman kedua
juga memiliki frekuensi pengiriman yang sama dengan pengiriman pertama, dimana
terjadi dua kali pengiriman di setiap pagi, siang, dan sore. Hal yang membedakan ske-
nario pengiriman pertama dan skenario pengiriman kedua yaitu dari sisi operasional
bahan bakar dan besarnya biaya investasi yang perlu dikeluarkan. Dengan adanya dua
skenario pengiriman yang ada, nantinya dapat dibandingkan skenario mana yang
menghasilkan keuntungan yang lebih baik untuk PT XYZ dibandingkan dengan skena-
rio lainnya.
3. Metodology
Dalam melakukan penelitian ini, tahapan-tahapan yang dilakukan dimulai dengan
mengidentifikasi permasalahan yang terjadi pada objek penelitian yaitu PT XYZ. Taha-
pan selanjutnya yaitu menentukan tujuan penelitian yang ingin dicapai dari permasala-
han yang terjadi. Setelah menentukan tujuan yang dicapai, selanjutnya melakukan studi
pustaka pada penelitian sebelumnya terkait solusi apa saya yang bisa dilakukan untuk
menyelesaikan permasalahan yang terjadi.
Membangun model matematis matematis menjadi salah satu tahapan penting yang
dilakukan pada penelitian ini. Hal ini dilakukan untuk memastikan, apakah model pe-
nyelesaian yang digunakan yaitu VRPTW sudah sesuai dan merepresentasikan dengan
permasalahan yang terjadi. Setelah model dinyatakan sesuai dengan permasalahan,
maka sebelum XXXX
3.1. Vehicle Routing Problem with Time Windows
Vehicle Routing Problem or commonly referred to as VRP, is a transportation model
problem that aims to solve the problem of determining the route by using several ve-
hicles and serving several customers in several different locations, where each customer
has their demands, and the vehicles that used to transport has it is own the vehicle ca-
pacity. The VRP model has several development model variations that adjusted to the
constraints and complexities of a problem.
Vehicle Routing Problem with Time Windows (VRPTW) is one of the VRP variations
that consider vehicle capacity limit and service time interval (time windows) in each
customer. VRPTW aims to minimize the total transportation cost by considering the ve-
hicle’s cost and traveling time matrixes. In the VRPTW model, there are two service time
types to can be used, i.e., hard time windows and soft time windows. However, in this
6. J. Open Innov. Technol. Mark. Complex.2021, 7, x FOR PEER REVIEW 6 of 20
research, the VRPTW model used was the hard time windows. In this model, when the
vehicle comes after the service time, then customers cannot serve the vehicle. This
VRPTW model fits with the problem in PT XYZ, because if the vehicle comes after the
service time, there are no employees who were serving it.
3.2. Model Formulation
The mathematical model formulation used in this research is the model of Vehicle
Routing Problem with Time Windows (VRPTW) that developed by Kallehauge in 2001
[6]. This model has purpose to minimize the total transportation costs with time windows
at each customer. The VRPTW mathematical model has a mathematical notation as fol-
lows:
: a set of vehicles with the same capacity
: a set of customers
: a set of points consisting customers and depots
: vehicle capacity
k: vehicle
i: customers demand
Cij: transportation costs from nodes i to nodes j
ij: travel timefrom nodes i to nodes j
Sik: starting timeof service at customers i
i: earliest time of service at customers i
i: latest time of service at customers i
The decision variable of the VRPTW mathematical model is:
7. 1, if there is a vehicle trip from i to j on route k
0, if there is no vehicle trip from i to j on route k
$
Then the objective function is:
min = '
22. J. Open Innov. Technol. Mark. Complex.2021, 7, x FOR PEER REVIEW 7 of 20
Based on the mathematical formulation above, equation 1 is an objective function of
the model to minimize travel costs. Equation 2 stated that each customer is visited once.
Equation 3 shows the limitation that a vehicle may not carry more than the vehicle's
capacity. Equation 4 shows that each vehicle starts from a depot. Equation 5 shows that
after visiting a customer, the vehicle will leave that customer and visit the next customer,
and equation 6 states that each vehicle will end up at the depot.Equation 7 is used to
express the relationship between the time of departure from customers and the time of
travel to the next customer. Equation 8 ensures that the time windows limit of each
customer is met and equation 9 states that the decision variable xijk is binary.
Based on the mathematical model above it is known that equation 7 is nonlinear,
therefore it needs to be changed to linear to verify the model. The linear equation is:
@
25. ∀., C ∈ , ∀2 ∈ (10)
Where constantan Mij can be derived tomax J
+
− K, (., C) ∈ L.
3.3. Metaheuristic Algorithm
3.3.1. SOS Algorithm
The SOS algorithm is an optimization technique adopted from the inter-organism
relationship pattern in its survival and proliferation [7]. Solution-seeking on the SOS al-
gorithm begins with the initial population, the so-called ecosystem, consisting of several
randomized individuals. These individuals will later pass three iterative seeking stages
to generate an optimum solution variable.
At each stage, each individual will interact randomly with one another to generate
solutions. Interaction results on each stage will be evaluated for their objective value to
obtain the best solution. The SOS algorithm’s seeking solution process will stop when the
termination criteria are met. The pseudocode from the Symbiotic Organisms Search al-
gorithm used in this research is presented in Figure X.
BF= = (1 + round (rand(0,1))
Step 1: Ecosystem Initialization
Step 2: For i = 1, 2, . . ., eco_size
Evaluate f(Xi)
Xbest = Minimum f(Xi)
If Obj (Xi) Obj (Xbest) do
Update Xbest = Xi
End if
Step 3:
Whileiteration (iter) maximum iteration (max iter) do
Fori = 1, 2, . . ., eco_size
Mutualism Phase
Select one organisme Xj randomly, where Xj ≠ Xi
Calculate benefit vector and mutual vector
BFQ = (1 + round (rand(0,1))
Mutual vector =
STSU
Q
26. J. Open Innov. Technol. Mark. Complex.2021, 7, x FOR PEER REVIEW 8 of 20
Figure X Pseudocode SOS
Figure X Cont.
XWXYZ = XW + rand(0,1) ∗ (XY]^ − X_)
X`aba]W^Y = rand (0,1) ∗ (UB − LB) + LB
Comensalism Phase
Select one organisme Xj randomly, where Xj ≠ Xi
Calculate Xinew
Decode Xinew
Evaluate f(Xinew)
If Obj Xinew Obj Xi do
Update Xi = Xinew
End If
Parasitism Phase
Select one organisme Xj randomly, where Xj ≠ Xi
Generate Xparasite from organism Xi
Generate r = random (0,1)
r parasite_force
Mutation Xi uses a random number with a range of [ub,lb]
Decode Xparasite Xparasite dan Xj
Evaluate f(Xparasite) and f(Xjnew)
If Obj Xparasite Obj Xj do
Update Xj = Xparasite
End If
End for
End while
27. J. Open Innov. Technol. Mark. Complex.2021, 7, x FOR PEER REVIEW 9 of 20
3.3.2. PSO Algorithm
The solution-seeking procedure on PSO was conducted by a population comprised
of several particles. Because PSO uses stochastics data, then the population within has to
be raised using random numbers with the lowest value and highest value limitations. In
seeking solutions, each particle conducts searching in the search space to find its par-
ticle's best position (local best) and the best position of all populations (global best).
Moving particles will be searching in the search space using dynamic velocity that tends
to move to the best searching area.
Each particle executes the best position-seeking process in several determined par-
ticular iteration. On each iteration, solutions represented by the particle position were
evaluated for their performance by entering the solution to the fitness function [8]. The
pseudocode from the Particle Swarm Optimization algorithm in this research is pre-
sented in Figure X.
Figure X Pseudocode PSO Algorithm
e
(f=) = e
(f) +
(f=)
Step 1 :
For each particle i : 1, 2, …N
Random initialization Xi
Random initialization Vi (or just set Vi to zero)
Evaluate the fitness of particle i, f(xi)
Evaluate Pbest and Gbest
End For
Step 2 :
While iteration (iter) maximum iteration (max iter)do
For each particle i : 1, 2, …N
Update Velocities with
(f=) = g
(f) + h='=?ij@
(f) − e
(f)B + hQ'Q?kj@
(f) − e
(f)B
Update Position with
Evaluate the fitness of particle i, f(xi)
If Pbest(t+1) Pbest(t) do
Pbest(t) = Pbest(t+1)
End If
Gbest(t+1) = small value in Pbest
If Gbest(t+1) Gbest(t) do
Gbest(t) = Gbest(t+1)
End For
End While
28. J. Open Innov. Technol. Mark. Complex.2021, 7, x FOR PEER REVIEW
3.4. Solution Representation
Solution representation determination is an important process in implementing a
metaheuristic algorithm. It is because the solution representation is the illustration r
presentation of the generated
creating a route to distribute raw materials from the CK to each outlet by not violating
the vehicle capacity limit and service time on each outlet.
The route began by vehicles departing from the
nodes that have demand less than the vehicle capacity. Another limitation of vehicles’
starting time on each node is also mandatory besides the vehicle capacity. If the vehicle
came after the outlet’s service time, the
Therefore, the vehicle could not be served on that node and had to find another node or
go back to the depot. One of the solution representation examples in this research is
presented in Figure X.
3.5. Feasibility Study Analysis
Feasibility study analysis is a procedure to assess, measure, and analyze the feas
bility of a policy plan or project to be executed [10]. In conducting a feasibility study,
there are three thin
and capital budgeting analysis. There are three methods to evaluate an investment’s fe
sibility in the capital budgeting analysis, namely NPV, PI, and PP. Solution represent
tion determination is an important process in implementing a metaheuristic algorithm. It
is because the solution representation is the illustration representation of the generated
solution [9]. The solution
raw materials from the CK to each outlet by not violating the vehicle capacity limit and
service time on each outlet.
3.5.1. Net Present Value (NPV) Model
It is a technique to estimate the company's generated profit in the future if we invest with t
current monetary value. The NPV calculation is as follows:
Where:
NPV : Net Present Value
Lf : Cash flow
i : Interest rate used
t : Project’s economist life, started from the initial stage to the end of
n : Reviewed project’s life
3.5.2. Profitability Index (PI) Method
It is a technique to estimate a project’s feasibility by comparing its net profit value
with the initial investment value. The profitability index calculation is as
, x FOR PEER REVIEW
Solution Representation
Solution representation determination is an important process in implementing a
metaheuristic algorithm. It is because the solution representation is the illustration r
presentation of the generated solution [9]. The solution-seeking in this research was by
creating a route to distribute raw materials from the CK to each outlet by not violating
the vehicle capacity limit and service time on each outlet.
The route began by vehicles departing from the depot, and then each vehicle went to
nodes that have demand less than the vehicle capacity. Another limitation of vehicles’
starting time on each node is also mandatory besides the vehicle capacity. If the vehicle
came after the outlet’s service time, the nodes violated the service time limitation.
Therefore, the vehicle could not be served on that node and had to find another node or
go back to the depot. One of the solution representation examples in this research is
presented in Figure X.
Figure X Representation Solution VRPTW Model
Feasibility Study Analysis
Feasibility study analysis is a procedure to assess, measure, and analyze the feas
bility of a policy plan or project to be executed [10]. In conducting a feasibility study,
there are three things to be considered, i.e., financial analysis, perceived benefit analysis,
and capital budgeting analysis. There are three methods to evaluate an investment’s fe
sibility in the capital budgeting analysis, namely NPV, PI, and PP. Solution represent
termination is an important process in implementing a metaheuristic algorithm. It
is because the solution representation is the illustration representation of the generated
solution [9]. The solution-seeking in this research was by creating a route to dist
raw materials from the CK to each outlet by not violating the vehicle capacity limit and
service time on each outlet.
Net Present Value (NPV) Model
It is a technique to estimate the company's generated profit in the future if we invest with t
current monetary value. The NPV calculation is as follows:
i =
Lf
(1 + .)f
;
fl5
(11)
Net Present Value
Cash flow on period t
: Interest rate used
: Project’s economist life, started from the initial stage to the end of
: Reviewed project’s life
Profitability Index (PI) Method
It is a technique to estimate a project’s feasibility by comparing its net profit value
with the initial investment value. The profitability index calculation is as
10 of 20
Solution representation determination is an important process in implementing a
metaheuristic algorithm. It is because the solution representation is the illustration re-
seeking in this research was by
creating a route to distribute raw materials from the CK to each outlet by not violating
depot, and then each vehicle went to
nodes that have demand less than the vehicle capacity. Another limitation of vehicles’
starting time on each node is also mandatory besides the vehicle capacity. If the vehicle
nodes violated the service time limitation.
Therefore, the vehicle could not be served on that node and had to find another node or
go back to the depot. One of the solution representation examples in this research is
entation Solution VRPTW Model
Feasibility study analysis is a procedure to assess, measure, and analyze the feasi-
bility of a policy plan or project to be executed [10]. In conducting a feasibility study,
gs to be considered, i.e., financial analysis, perceived benefit analysis,
and capital budgeting analysis. There are three methods to evaluate an investment’s fea-
sibility in the capital budgeting analysis, namely NPV, PI, and PP. Solution representa-
termination is an important process in implementing a metaheuristic algorithm. It
is because the solution representation is the illustration representation of the generated
seeking in this research was by creating a route to distribute
raw materials from the CK to each outlet by not violating the vehicle capacity limit and
It is a technique to estimate the company's generated profit in the future if we invest with the
: Project’s economist life, started from the initial stage to the end of project’s life
It is a technique to estimate a project’s feasibility by comparing its net profit value
with the initial investment value. The profitability index calculation is as follows:
29. J. Open Innov. Technol. Mark. Complex.2021, 7, x FOR PEER REVIEW 11 of 20
PI =
PV of future cash plow
PV of investment
(12)
Where:
PI : Profitability index
PV of future cash flow : Present value of future cash flow
PV of investment : Initial Investment
3.5.3. Payback Period (PP) Method
It is a technique used to assess the period of return on investment. The payback pe-
riod calculation is as follows:
PP =
Cost of Investment
Annual cashplow
x 1 year (13)
Where:
PP : Payback period
4. Result and Discussion
Data used in this research were divided into two, i.e., small instance and large in-
stance data. The small instance data shows data for one-time delivery frequency, while
the large instance data shows delivery scenario data in a day. The large instance data it-
self is data processed following the delivery frequency to be implemented. This data was
made by dividing each customer’s demand based on the delivery time and adjusted to
vehicle capacity. In this research, the large instance data was categorized into two, i.e.,
large instance 50 kg and large instance 250 kg. The large instance 50 kg was the data used
in the first delivery scenario using two-wheeled motor vehicles and a delivery box of 50
kg capacity. Meanwhile, the large instance 250 kg data was used in the second scenario
using three-wheeled motor vehicles with a maximum capacity 250 kg.
The data processing in this research used AMPL software with a GUROBI solver to
verify the mathematical model. Meanwhile, for SOS and PSO metaheuristic methods
program, Visual Studio of 2019 with C# programming language was used. Another
software used was SPSS 16.0 to test statistical analysis. The computer used in this re-
search was Lenovo C340 with specifications of intel core i3-10110U processor, RAM 8 GB,
and system windows 10 64-bit.
4.1. Verification and Validation Model
Model verification was conducted to ensure that the objective function and con-
straints of the model are mathematically accurate and logically consistent. Meanwhile,
model validation was conducted to ensure that the mathematical model computation
will generate the same output as manual calculation. Model verification and validation
were conducted using the AMPL software, which declared that the model was verified
and validated. The verification was proven by the absence of sub-routes or errors on the
generated output. The model was also validated because it had the same value as the
results of manual calculation. The verification and validation processes for the small in-
stance data produce an optimum solution with an objective value of 4240.
4.2. Parameter Tuning
Parameter tuning was conducted to discover the parameter combination that gene-
rates the best solution quality with short computation times. In this research, parameter
value was determined before the algorithm was running, so-called off-line tuning. The
parameter tuning method used in this research was the One Factor at A Time (OFAT),
where one parameter will be tested for each value and assuming that other untested pa-
30. J. Open Innov. Technol. Mark. Complex.2021, 7, x FOR PEER REVIEW 12 of 20
rameters have fixed values. Parameter value determination for both metaheuristic me-
thods was adopted from a literature review of previous research. Parameter values used
in this research are shown in Table 1.
Table
1.Parameter
Values of
SOS and
PSO Algo-
rithms
All parameter values in Table 1 were combined with each other to be analyzed for
their parameter sensitivity. The parameter sensitivity analysis was made to discover the
effect of a parameter on its solution quality and computation time length. The result of
sensitivity analysis is discovering the best value of each parameter in solving the VRPTW
problem.
Based on the sensitivity analysis results, the best parameter value in the SOS algo-
rithm for maxiter value is 1000, eco size 50, and parasite force (pf) 0.7. Meanwhile, the
PSO algorithm has the best maxiter value 500, inertia weight (w) 1, swarm size (N) 20,
and cognitive and social factors with the same value 2.
4.3. Verification and Validation Algorithm
By using the best parameter value combination, the next step was to verify and va-
lidate algorithms. Algorithm verification and validation were conducted by comparing
the results of the objective values obtained from SOS and PSO algorithms with the objec-
tive values from the exact method. The verification and validation results are shown in
Table 2. The table shows that SOS and PSO algorithms can generate the same objective
values as a result of the exact method.
Table 2.Computation Results of SOS and PSO Algorithms for the Small Instance Data
Instance
Exact Method SOS Algorithm PSO Algorithm
Objective Value Objective Value Objective Value
Small - 1 4240 4240 4240
Small - 2 4240 4240 4240
Small - 3 4240 4240 4240
Small - 4 4240 4240 4240
Small - 5 4240 4240 4240
Small - 6 4240 4240 4240
Small - 7 4240 4240 4240
Algorithm Parameter Value
SOS
Maxiter 500 1000 1500
Eco Size 25 50 75
Parasite Force (pf) 0.7 0.8 0.9
PSO
Maxiter 500 1000
Inertia Weight (w) 0.25 0.5 1
Swarm Size (N) 20 40 80
Cognitive Factor 1 2
Social Factor 1 2
31. J. Open Innov. Technol. Mark. Complex.2021, 7, x FOR PEER REVIEW 13 of 20
4.4. Computational Result
Based on algorithm verification and validation results, it can be known that SOS and
PSO algorithms can generate an optimum solution for the small instance data. Therefore,
these two algorithms can be used to solve the VRPTW problem in the distribution prob-
lem of PT XYZ. The results of SOS and PSO algorithms using the best parameter combi-
nation are shown in Table 3 and Table 4.
Table 3.Computational Result of SOS and PSO Algorithms for Large Instance 50 kg
Instance
SOS PSO
Best
Obj.
Average
Obj.
CPU
Time (s)
Best
Obj.
Average
Obj.
CPU
Time (s)
Large 50 -1 7691 9639 4.82 10758 15032 1.35
Large 50 -2 13379 14470 2.67 10997 11144 1.42
Large 50 -3 12795 15129 2.77 11348 12654 1.72
Large 50 -4 13683 14943 2.46 11568 13384 1.80
Large 50 -5 11777 12620 2.41 12458 13882 1.39
Large 50 -6 11057 12643 2.63 11032 12548 1.63
Large 50 -7 12300 12913 2.75 11361 14478 2.05
Average 11812 13194 2.93 11360 13303 1.62
Table 4.Computational Result of SOS and PSO Algorithms for Large Instance 250 kg
Instance
SOS PSO
Best
Obj.
Average
Obj.
CPU
Time (s)
Best
Obj.
Average
Obj.
CPU
Time (s)
Large 250 -1 19471 21035 2.28 14823 17822 1.86
Large 250 -2 17415 19664 2.41 18486 21756 1.26
Large 250 -3 20243 23442 4.17 17952 20787 1.88
Large 250 -4 19109 23085 4.99 21763 22756 1.87
Large 250 -5 17866 19529 5.22 17801 18793 1.73
Large 250 -6 21291 22028 4.68 20009 20643 1.25
Large 250 -7 17137 18529 2.67 19407 20907 2.16
Average 18933 21045 3.77 18606 20495 1.71
4.5. Statistical Analysis
The statistical analysis test was conducted to measure the solution quality perfor-
mance generated by each metaheuristic algorithm. The purpose of the statistical analysis
test is to determine the difference in average objective values of each algorithm. Testing
using statistical analysis began by conducting the normality test, homogeneity test, and
paired t-test.
4.5.1. Normality Test
The first testing was the normality test, where it was conducted to discover that the
tested data are normally distributed. The hypothesis used in this testing were as follow:
32. J. Open Innov. Technol. Mark. Complex.2021, 7, x FOR PEER REVIEW 14 of 20
H0 = Data are distributed normally
H1 = Data are not distributed normally
α = 0.05
The normality test results are shown in Table 5, showing all four tested data have a
p-value (sig.) bigger than the value of α = 0.05. It is then concluded that H0 is accepted, or
the data are distributed normally.
Table 5.Results of Normality Test for the Large Instance 50 kg Data and Large Instance 250 kg Data
Algorithm
Shapiro - Wilk
Statistic df Sig
Objective
SOS 50kg 0.882 7 0.235
PSO 50kg 0.976 7 0.939
SOS 250kg 0.934 7 0.588
PSO 250kg 0.944 7 0.680
4.5.2. Normality Test Homogeneity Test
The second performance test was the homogeneity test, it was conducted to test the
variance homogeneity of data. The hypothesis used in this test were as follow:
H0 = Data variance are homogenous
H1 = Data variance are not homogenous
α = 0.05
The homogeneity test results are shown in Table 6 and Table 7, showing all four
tested data have p-value (sig) bigger than the value of α = 0.05. The decision made is that
H0 is accepted, or the data variance is homogenous.
Table 6.Results of Homogeneity Tests of the Large Instance 50 kg Data
Objective
Levene Statistic Sig.
Based on Mean 0.618 0.447
Based on Median 0.466 0.508
Based on Median and with adjusted df 0.466 0.511
Based on trimmed mean 0.678 0.426
Table 7.Results of Homogeneity Test of the Large Instance 250 kg Data
Objective
Levene Statistic Sig.
Based on Mean 0.351 0.565
Based on Median 0.480 0.502
Based on Median and with adjusted df 0.480 0.503
Based on trimmed mean 0.371 0.554
4.5.3. Normality Test Paired T-test
The last test was the paired t-test, where it was conducted to test the parametric
difference on two paired data. The computational result of the SOS algorithm in large
instance 50 kg was paired with the computational result of the PSO algorithm in large
instance 50 kg. The paired t-test was also conducted for the computational result of the
33. J. Open Innov. Technol. Mark. Complex.2021, 7, x FOR PEER REVIEW 15 of 20
large instance 250 kg SOS and the computational result of the large instance 250 kg PSO.
The hypothesis used in this research were as follow:
H0 = There is not a statistically significant difference
H1 = There is a statistically significant difference
α = 0.05
The results of the paired t-test are shown in Table 8, where pair 1, the relationship
between the large instance 50 kg data of SOS and large instance 50 kg data of PSO, has a
p-value = 0.925. Meanwhile, pair 2, the relationship between the large instance 250 kg
data of SOS and large instance 250 kg data of PSO, has a p-value = 0.525. From both pairs,
it is discovered that all p-values (sig.) are bigger than the value of α = 0.05. So it is con-
cluded that H0 is accepted. It shows there is not a statistically significant difference be-
tween the results of the SOS and PSO algorithms for both data.
Table 8.Results of Paired Samples Test for SOS and SPO Algorithms
Pair t df Sig.(2-tailed)
Pair 1 SOS 50kg - PSO 50kg -0.098 6 0.925
Pair 2 SOS 250kg - PSO 250kg 0.675 6 0.525
Based on the statistical analysis results, it can be concluded that even though there
are differences between objective values generated by SOS and PSO algorithms, with the
statistical analysis test shown, the differences are insignificant. Therefore, to discover
which algorithm generates the best solution, it is necessary to conduct a test for the
computation time.
The computational time result can be seen in Table 3 and Table 4, where the PSO
algorithm in Large Instance 50 kg and Large Instance 250 kg had shorter computational
time than the SOS algorithm. So, it can be concluded that the PSO algorithm can get the
solution that tends to optimal with short computational time. This research proves that
the PSO algorithm to solve the Vehicle Routing Problem with Time Windows produces a
better solution than the SOS algorithm.
4.6. Implementation of Metaheuristic Method
Based on statistical analysis results, knowing that the PSO algorithm generates bet-
ter objective values with a short computation time than the SOS algorithm. Hence, the
PSO algorithm results to be used do represent the route determination result using me-
taheuristic methods. The results of PSO algorithm implementation on large instance 50
kg and large instance 250 kg data for 7-days delivery are shown in Table 9.
Table 9.Results of PSO Algorithm for 7-Days Delivery
Day Data
Objec-
tive
Route
1
50 10758
26-21-20-19-22-24-23-29-6-5-18-13-14-8-9-30-25-27-28-15-16-1
2-11-10-7-4-3-2-17-1
250 14823
26-25-21-22-19-20-24-23-30-29-3-8-9-15-16-13-17-18-12-11-10-
7-6-5-4-2-27-28-14-1
2
50 10997
1-2-14-16-15-11-29-28-25-30-4-5-3-13-18-17-10-9-19-20-21-22-2
3-24-8-26-27-7-12-6
250 18486
2-26-20-19-24-23-30-9-8-7-13-18-17-16-14-15-25-27-28-21-22-2
9-12-11-10-6-5-4-3-1
34. J. Open Innov. Technol. Mark. Complex.2021, 7, x FOR PEER REVIEW 16 of 20
3
50 11348
12-11-26-27-25-2-5-28-29-30-4-14-13-15-9-16-17-18-19-20-21-2
2-23-24-8-7-6-3-10-1
250 17952
4-1-25-19-22-21-20-27-29-3-2-13-14-15-16-17-18-28-26-30-11-1
2-10-9-8-7-23-24-6-5
4
50 11568
4-25-26-20-19-22-23-24-28-30-27-29-2-1-5-10-7-21-15-13-14-16-
17-18-12-11-9-8-6-3
250 21763
7-9-1-2-6-25-19-20-30-10-14-15-16-13-5-28-22-21-24-23-29-18-1
7-8-12-3-26-27-11-4
5
50 12458
2-3-28-22-23-24-25-26-27-29-1-9-12-15-14-19-21-20-30-13-16-1
7-18-11-10-8-7-6-5-4
250 17801
1-7-15-14-13-17-11-12-2-5-6-8-25-26-30-3-16-18-19-20-21-22-23
-24-10-9-27-28-29-4
6
50 11032
28-25-29-21-20-19-2-5-10-27-26-22-24-23-30-7-8-13-14-15-16-1
7-18-9-12-11-6-4-3-1
250 20009
7-9-25-29-3-4-16-14-17-2-1-28-26-27-30-6-13-15-8-10-12-11-18-
19-20-21-22-23-24-5
7
50 11361
27-26-25-29-11-12-2-10-7-9-30-19-22-23-24-13-14-15-16-17-18-
8-28-20-21-6-5-4-3-1
250 19407
2-20-19-27-30-12-13-14-15-16-17-25-28-26-29-6-3-1-10-9-21-22-
23-24-18-7-8-11-5-4
4.7. Comparison Total Cost of Existing and Solution Routes
After obtaining the total cost for each delivery day and vehicle route to be taken, the
next step was to compare the total cost generated by the proposed route versus the ex-
isting transportation cost. The comparison is shown in Table 10.
Table 10.Comparison Total Cost of Existing and Solution Routes
Day
Total Cost
Current
Method
Total Cost Scenario 1 Total Cost Scenario 2
50kg GAP (%) 250kg GAP (%)
1 Rp25.000 Rp10.758 56,97% Rp14.823 40,71%
2 Rp25.000 Rp10.997 56,01% Rp18.486 26,06%
3 Rp25.000 Rp11.348 54,61% Rp17.952 28,19%
4 Rp25.000 Rp11.568 53,73% Rp21.763 12,95%
5 Rp25.000 Rp12.458 50,17% Rp17.801 28,80%
6 Rp25.000 Rp11.032 55,87% Rp20.009 19,96%
7 Rp25.000 Rp11.361 54,56% Rp19.407 22,37%
Based on Table 10, it can be seen that the proposed total cost is lower than the ex-
isting total cost. The gap between the first proposed scenario total cost with the existing
total cost ranges from 50% to 56%. Meanwhile, it ranges from 12% to 40% for the second
proposed scenario total cost compared to the existing total cost. Hence, route determina-
tion in the two proposed scenarios can minimize the transportation cost rather than the
existing method.
35. J. Open Innov. Technol. Mark. Complex.2021, 7, x FOR PEER REVIEW 17 of 20
4.8. Investment Feasibility Analysis
The investment feasibility analysis was conducted to discover which scenario, first
or second, that gives profit to the company, whether financial or benefit-wise. In con-
ducting an investment feasibility analysis, the steps conducted are calculating investment
feasibility based on financial analysis and capital budgeting. An analysis of perceived
benefits from the investment plan was also conducted.
4.8.1. Cost Analysis
Cost analysis was conducted to find out the cash flow in a company. There are four
considerations in a company’s financial statements, i.e., investment cost, operational cost,
revenue, and depreciation cost. These four costs are calculated during the vehicle’s eco-
nomic life. The results of cost analysis are a financial statement and net cash flow of the
company when executing the planned investment.
4.8.2. Capital Budgeting Analysis
Capital budgeting was used to determine the acceptance or rejection of an invest-
ment plan to be executed. An investment plan’s feasibility is a consideration in deter-
mining a policy or plan to be carried out. In this research, the capital budgeting methods
used were the net present value (NPV), profitability index (PI), and payback period (PP).
The first and second scenarios calculation results using three capital budgeting methods
are shown in Table 11.
Table 11.Result of Investment Feasibility Analysis
Indicator Criteria
Scenario 1 Scenario 2
Value Decision Value Decision
NPV NPV 0 (Rp 28.299.974)
Not
Feasible
Rp9.149.022 Feasible
Profitability
Index
PI 1 0,739
Not
Feasible
1,112 Feasible
Payback
Period
PP Useful
Life
5 years
Not
Feasible
7,63 years Feasible
Based on Table 11, it is discovered that the first scenario is not feasible to be im-
plemented because the resulting calculation values are not fulfilling all criteria of capital
budgeting calculation methods. In contrast, the second scenario is declared feasible be-
cause the resulting calculation values fulfill all criteria of capital budgeting methods.
4.8.3. Benefit Analysis
A benefit analysis was conducted to discover the company’s perceived benefits by im-
plementing the new distribution system. The perceived benefits are:
1. Saving in distribution costs
By implementing the new distribution method, the company only spent a trans-
portation cost of IDR 18,606. Cost is less than the current transportation cost of the
company for IDR 25,000.
36. J. Open Innov. Technol. Mark. Complex.2021, 7, x FOR PEER REVIEW 18 of 20
2. Delivery scheduling
By determining a schedule, the delivery becomes six times per day. It makes the
distribution system more organized and clearer.
3. Optimum operator working time
By implementing the new policy, it will optimize each operator’s working time. The
time can be maximized according to the determined operator’s working time.
4. Product delivery data
With the new policy, delivery is entirely operated by the CK. It will avoid discre-
pancy of inventory in CK.
5. Financial Statement
Different from the current distribution method, this new distribution method has
established the fuel and maintenance costs from the beginning. Thus, the monthly
financial statement will be more organized and clearer.
5. Conclusions
The solution quality resulted from the SOS algorithm has an insignificant difference
with the solution quality PSO algorithm. However, in computation speed to reach the
convergent point, the PSO algorithm has a relatively faster time than the SOS algorithm.
Thus, the PSO algorithm will be implemented on the route determination problem of PT
XYZ. By conducting route determination using metaheuristic approach methods, it saves
daily distribution cost of 56% for the first scenario and 40% for the second scenario. Based
on the feasibility analysis results, the second delivery scenario using three-wheeled mo-
tor vehicles is more feasible to be executed than the first scenario using motor vehicles
with a delivery box. It is proven based on the calculation results using capital budgeting
methods where resulting values fulfill are feasibility criteria in conducting an investment.
Future research may apply and testing SOS and PSO algorithms performance in
another optimization problem, especially in Vehicle Routing Problem (VRP) variations.
Evaluating solution quality and computation times using both algorithms can be sup-
ported by programming skills and better computer specifications. On the other hand, to
get a better solution and computational times, future research may consider other para-
meter values or other parameter tuning methods.
37. J. Open Innov. Technol. Mark. Complex.2021, 7, x FOR PEER REVIEW 19 of 20
6. Patents
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the work reported in this manuscript.
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title, Table S1: title, Video S1: title.
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Appendix A
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References
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1. Author 1, A.B.; Author 2, C.D. Title of the article. Abbreviated Journal NameYear, Volume, page range.
2. Author 1, A.; Author 2, B. Title of the chapter. In Book Title, 2nd ed.; Editor 1, A., Editor 2, B., Eds.; Publisher: Publisher Loca-
tion, Country, 2007; Volume 3, pp. 154–196.
3. Author 1, A.; Author 2, B. Book Title, 3rd ed.; Publisher: Publisher Location, Country, 2008; pp. 154–196.
4. Author 1, A.B.; Author 2, C. Title of Unpublished Work. Abbreviated Journal Name stage of publication (under review; accepted;
in press).
5. Author 1, A.B. (University, City, State, Country); Author 2, C. (Institute, City, State, Country). Personal communication, 2012.
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