This article appeared in a journal published by Elsevier. The .docxhowardh5
This article appeared in a journal published by Elsevier. The attached
copy is furnished to the author for internal non-commercial research
and education use, including for instruction at the authors institution
and sharing with colleagues.
Other uses, including reproduction and distribution, or selling or
licensing copies, or posting to personal, institutional or third party
websites are prohibited.
In most cases authors are permitted to post their version of the
article (e.g. in Word or Tex form) to their personal website or
institutional repository. Authors requiring further information
regarding Elsevier’s archiving and manuscript policies are
encouraged to visit:
http://www.elsevier.com/authorsrights
http://www.elsevier.com/authorsrights
Author's personal copy
A simheuristic algorithm for the Single-Period Stochastic
Inventory-Routing Problem with stock-outs
Angel A. Juan a,⇑, Scott E. Grasman b, Jose Caceres-Cruz a,1, Tolga Bektas� c
a Department of Computer Science, Multimedia, and Telecommunication, IN3-Open University of Catalonia, 08018 Barcelona, Spain
b Department of Industrial and Systems Engineering, Rochester Institute of Technology, USA
c Southampton Management School and Centre for Operational Research, Management Science and Information Systems (CORMSIS), University of Southampton, UK
a r t i c l e i n f o
Article history:
Available online 7 December 2013
Keywords:
Inventory-Routing Problem
Stochastic demands
Stock-outs
Simulation–optimization
Simheuristics
Randomized heuristics
a b s t r a c t
This paper describes a ‘simheuristic’ algorithm – one which combines simulation with
heuristics – for solving a stochastic variant of the well-known Inventory-Routing Problem.
The variant discussed here is integrated by a vehicle routing problem and several inventory
problems characterized by stochastic demands. Initial stock levels and potential stock-outs
are also considered, as well as a set of alternative refill policies for each retail center. The
goal is to find the personalized refill policies and associated routing plan that minimize, at
each single period, the expected total costs of the system, i.e., the sum of inventory and
routing costs. After motivating it, a detailed description of the problem is provided. Then,
a review of the related literature is performed and our simulation–optimization approach
is introduced. The paper presents a set of numerical experiments comparing the proposed
method against different refill strategies and discusses how total costs evolve as the level of
system uncertainty and the inventory-holding costs per unit are varied.
� 2013 Elsevier B.V. All rights reserved.
1. Introduction
One of the most important paradigms in supply chain management is to move from sequential decision making toward
integrated decision making, where all parties in the supply chain determine the best policy for the entire system. This is in
contrast to sequentially optimized decisions in supply chains.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A global economy and increase in customer expectations in terms of cost and services
have put a premium on eective supply chain reengineering. It is essential to perform
risk benet analysis of reengineering alternatives before making a nal decision. Sim-
ulation provides an eective pragmatic approach to detailed analysis and evaluation of
supply chain design and management alternatives. However, the utility of this method-
ology is hampered by the time and eort required to develop models with sucient
delity to the actual supply chain of interest. In this paper, we describe a supply-chain
modeling framework designed to overcome this diculty. Using our approach, supply
chain models are composed from software components that represent types of supply
chain agents (like retailers, manufacturers, transporters), their constituent control ele-
ments (like inventory policy), and their interaction protocols (like message types). The
underlying library of supply chain modeling components has been derived from anal-
ysis of several dierent supply chains. It provides a reusable base of domain-specic
primitives that enables rapid development of customized decision support tools.
We have always been the learning hub for the students -going to be professionals. Every year we provide opportunity to the students to acquire industrial and corporate training which helps both in their academic purpose as well as their professional career. They are given the rigorous training on their subject specialization at the same time focusing on their character and attitude development which grooms their personality to be suitable for the corporate sector.
Here are the projects of our SIPs of Transports and Logistics Management.
Design and Optimization of Supply Chain Network with Nonlinear Log-Space Mode...RSIS International
This proposal intends to address the practical vulnerabilities in the state-of-the-art models for optimal design of supply chain network. While the conventional models attempt to transform the design constraints of the supply chain network into sum of cost functions, the proposed model will transform the cost function into a nonlinear subspace. Moreover, the subspace will be optimized under a logarithmic scale and so the multiple network constraints such as stock transportation, inventory, echelon levels and backorders can be mapped within the subspace. Subsequently, robust optimization algorithms based on biological inspiration will be proposed. The optimization algorithms will be included with adaptiveness and so the nonlinear cost function can be solved effectively. The adaptiveness will be mainly based on the ability of handing every network constraints such as echelon levels, inventory, etc
Omni-Channel Distribution: A Transshipment Modeling Perspectiveijmvsc
In our work, we develop a specialized optimization technique that adapts the general linear programming Transshipment model to the ever-growing needs of Omni-Channel distribution in Supply Chain Management. With the rapid adoption of “smart” mobile technologies, customers now acquire merchandise across multiple channels and devices. As a result, retailers are challenged with downstream operational complexities.
Fulfillment of customer orders now changes the placement and amount of independent demand inventory organizations may hold. Our research integrates the use of Hub or Fulfillment Centers, locations where sellers fill customer orders placed through e-commerce, as an additional segment of demand. This adaptation to the optimization of Transshipment can result in significant benefits to the firm’s logistics presence, customer retention, and profit.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
This article appeared in a journal published by Elsevier. The .docxhowardh5
This article appeared in a journal published by Elsevier. The attached
copy is furnished to the author for internal non-commercial research
and education use, including for instruction at the authors institution
and sharing with colleagues.
Other uses, including reproduction and distribution, or selling or
licensing copies, or posting to personal, institutional or third party
websites are prohibited.
In most cases authors are permitted to post their version of the
article (e.g. in Word or Tex form) to their personal website or
institutional repository. Authors requiring further information
regarding Elsevier’s archiving and manuscript policies are
encouraged to visit:
http://www.elsevier.com/authorsrights
http://www.elsevier.com/authorsrights
Author's personal copy
A simheuristic algorithm for the Single-Period Stochastic
Inventory-Routing Problem with stock-outs
Angel A. Juan a,⇑, Scott E. Grasman b, Jose Caceres-Cruz a,1, Tolga Bektas� c
a Department of Computer Science, Multimedia, and Telecommunication, IN3-Open University of Catalonia, 08018 Barcelona, Spain
b Department of Industrial and Systems Engineering, Rochester Institute of Technology, USA
c Southampton Management School and Centre for Operational Research, Management Science and Information Systems (CORMSIS), University of Southampton, UK
a r t i c l e i n f o
Article history:
Available online 7 December 2013
Keywords:
Inventory-Routing Problem
Stochastic demands
Stock-outs
Simulation–optimization
Simheuristics
Randomized heuristics
a b s t r a c t
This paper describes a ‘simheuristic’ algorithm – one which combines simulation with
heuristics – for solving a stochastic variant of the well-known Inventory-Routing Problem.
The variant discussed here is integrated by a vehicle routing problem and several inventory
problems characterized by stochastic demands. Initial stock levels and potential stock-outs
are also considered, as well as a set of alternative refill policies for each retail center. The
goal is to find the personalized refill policies and associated routing plan that minimize, at
each single period, the expected total costs of the system, i.e., the sum of inventory and
routing costs. After motivating it, a detailed description of the problem is provided. Then,
a review of the related literature is performed and our simulation–optimization approach
is introduced. The paper presents a set of numerical experiments comparing the proposed
method against different refill strategies and discusses how total costs evolve as the level of
system uncertainty and the inventory-holding costs per unit are varied.
� 2013 Elsevier B.V. All rights reserved.
1. Introduction
One of the most important paradigms in supply chain management is to move from sequential decision making toward
integrated decision making, where all parties in the supply chain determine the best policy for the entire system. This is in
contrast to sequentially optimized decisions in supply chains.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A global economy and increase in customer expectations in terms of cost and services
have put a premium on eective supply chain reengineering. It is essential to perform
risk benet analysis of reengineering alternatives before making a nal decision. Sim-
ulation provides an eective pragmatic approach to detailed analysis and evaluation of
supply chain design and management alternatives. However, the utility of this method-
ology is hampered by the time and eort required to develop models with sucient
delity to the actual supply chain of interest. In this paper, we describe a supply-chain
modeling framework designed to overcome this diculty. Using our approach, supply
chain models are composed from software components that represent types of supply
chain agents (like retailers, manufacturers, transporters), their constituent control ele-
ments (like inventory policy), and their interaction protocols (like message types). The
underlying library of supply chain modeling components has been derived from anal-
ysis of several dierent supply chains. It provides a reusable base of domain-specic
primitives that enables rapid development of customized decision support tools.
We have always been the learning hub for the students -going to be professionals. Every year we provide opportunity to the students to acquire industrial and corporate training which helps both in their academic purpose as well as their professional career. They are given the rigorous training on their subject specialization at the same time focusing on their character and attitude development which grooms their personality to be suitable for the corporate sector.
Here are the projects of our SIPs of Transports and Logistics Management.
Design and Optimization of Supply Chain Network with Nonlinear Log-Space Mode...RSIS International
This proposal intends to address the practical vulnerabilities in the state-of-the-art models for optimal design of supply chain network. While the conventional models attempt to transform the design constraints of the supply chain network into sum of cost functions, the proposed model will transform the cost function into a nonlinear subspace. Moreover, the subspace will be optimized under a logarithmic scale and so the multiple network constraints such as stock transportation, inventory, echelon levels and backorders can be mapped within the subspace. Subsequently, robust optimization algorithms based on biological inspiration will be proposed. The optimization algorithms will be included with adaptiveness and so the nonlinear cost function can be solved effectively. The adaptiveness will be mainly based on the ability of handing every network constraints such as echelon levels, inventory, etc
Omni-Channel Distribution: A Transshipment Modeling Perspectiveijmvsc
In our work, we develop a specialized optimization technique that adapts the general linear programming Transshipment model to the ever-growing needs of Omni-Channel distribution in Supply Chain Management. With the rapid adoption of “smart” mobile technologies, customers now acquire merchandise across multiple channels and devices. As a result, retailers are challenged with downstream operational complexities.
Fulfillment of customer orders now changes the placement and amount of independent demand inventory organizations may hold. Our research integrates the use of Hub or Fulfillment Centers, locations where sellers fill customer orders placed through e-commerce, as an additional segment of demand. This adaptation to the optimization of Transshipment can result in significant benefits to the firm’s logistics presence, customer retention, and profit.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
Optimization of Physical Distribution of Consumer Goods in Nigeria: A Case St...IOSR Journals
The study is aimedat procuring optimalsolutions to challenges faced in the physical distribution system of consumer goods in Nigeria context also the need to minimize cost especially in Physical distribution is inevitable as increased cost of transport and poor transport infrastructure imposes strain on the physical distribution system. The researcher applied network optimization models to develop optimal solutions to real life problems in physical distribution system. Using questionnaires the researcher was able to explain how various service variables influence the service level.The researcher identified trends in warehousing operations, the nature of the relationship between physical flow and distribution cost and how various service variables influenced the service level. Afterwards, he recommended ways to benefit from these opportunitiesand steps to take to cub the impact of its challenges of the physical distribution system.
STRATEGIES OF DELAY DELIVERY AND CONTROLLABLE LEAD TIME IN SUPPLY CHAIN CONSI...IAEME Publication
This paper describes about two strategies in consignment inventory based supply
chain with controllable lead time and delaying last delivery comprising a two level
supply chain involving single vendor and multi buyers. This model would give
minimum joint total expected cost of the strategies involving vendor and buyer,
simultaneously to optimize quantitative decision variables. Numerical examples are
presented to demonstrate the benefit of the proposed strategies and the effect of
changes on the cost and parameters are studied.
Bayesian approach for spare parts replenishment policies under uncertaintiesIJERD Editor
The legislative constraints, the need to optimize the dismantling process, the introduction of recycled
parts on the spare parts market are reinforced since the systems in end-of-life phase have become increasingly
profitable. There are few works that treat recycled spare parts integration problem in economic models of
inventory control. These works do not consider uncertainty. In order to manage more realistically the inventory
control of spare parts, we propose a probabilistic model formalized by a Bayesian network. The model is used to
identify the best purchase policy. More precisely, it allows choosing the best proportions between new spare
parts (NSP) and recycled spare parts (RSP) by taking into account the traditional criteria of inventory control
and the availability of the spare parts on the market. The proposed method provides a decision-making tool for
manufacturers who are interested both in reducing the costs of stocks and guaranteeing a minimal availability in
an uncertain environment.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
Introduction to LPC - Facility Design And Re-Engineeringthomas851723
Here is a presentation on Introduction to LPC - Facility Design And Re-Engineering. LPC has helped multiple clients globally in the design or re-engineering of existing facilities.
Optimization of Physical Distribution of Consumer Goods in Nigeria: A Case St...IOSR Journals
The study is aimedat procuring optimalsolutions to challenges faced in the physical distribution system of consumer goods in Nigeria context also the need to minimize cost especially in Physical distribution is inevitable as increased cost of transport and poor transport infrastructure imposes strain on the physical distribution system. The researcher applied network optimization models to develop optimal solutions to real life problems in physical distribution system. Using questionnaires the researcher was able to explain how various service variables influence the service level.The researcher identified trends in warehousing operations, the nature of the relationship between physical flow and distribution cost and how various service variables influenced the service level. Afterwards, he recommended ways to benefit from these opportunitiesand steps to take to cub the impact of its challenges of the physical distribution system.
STRATEGIES OF DELAY DELIVERY AND CONTROLLABLE LEAD TIME IN SUPPLY CHAIN CONSI...IAEME Publication
This paper describes about two strategies in consignment inventory based supply
chain with controllable lead time and delaying last delivery comprising a two level
supply chain involving single vendor and multi buyers. This model would give
minimum joint total expected cost of the strategies involving vendor and buyer,
simultaneously to optimize quantitative decision variables. Numerical examples are
presented to demonstrate the benefit of the proposed strategies and the effect of
changes on the cost and parameters are studied.
Bayesian approach for spare parts replenishment policies under uncertaintiesIJERD Editor
The legislative constraints, the need to optimize the dismantling process, the introduction of recycled
parts on the spare parts market are reinforced since the systems in end-of-life phase have become increasingly
profitable. There are few works that treat recycled spare parts integration problem in economic models of
inventory control. These works do not consider uncertainty. In order to manage more realistically the inventory
control of spare parts, we propose a probabilistic model formalized by a Bayesian network. The model is used to
identify the best purchase policy. More precisely, it allows choosing the best proportions between new spare
parts (NSP) and recycled spare parts (RSP) by taking into account the traditional criteria of inventory control
and the availability of the spare parts on the market. The proposed method provides a decision-making tool for
manufacturers who are interested both in reducing the costs of stocks and guaranteeing a minimal availability in
an uncertain environment.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
Introduction to LPC - Facility Design And Re-Engineeringthomas851723
Here is a presentation on Introduction to LPC - Facility Design And Re-Engineering. LPC has helped multiple clients globally in the design or re-engineering of existing facilities.
1. PRESENTERS: AKSHAY BHARDWAJ KSHITIJ PADHYE SRIKANTH CHADA 4/16/2009 On the Interactions Between Routing andInventory-Management Policies in a One-WarehouseN-Retailer Distribution System Leroy B. Schwarz, James E. Ward, Xin Zhai Krannert Graduate School of Management, Purdue University, West Lafayette, Indiana MANUFACTURING & SERVICE OPERATIONS MANAGEMENT Vol. 8, No. 3, Summer 2006, pp. 253–272 issn 1523-4614 eissn 1526-5498 06 0803 025
2. 4/16/2009 GOAL This paper examines the interactions between routing and inventory-management decisions in a two-level supply chain consisting of a cross-docking warehouse and N retailers. The authors’ goal is to determine a combined system inventory-replenishment, routing, and inventory allocation policy that minimizes the total expected cost/period of the system over an infinite time horizon.
3.
4. Dynamic Allocation of Inventory.Thanks to advancements in technology (e.g. RFID at Wal-Mart and dynamic truck routing by Schneider Trucking), the above can be implemented.
5. PROCEDURE The authors demonstrated that the optimal static route is not the shortest-total-distance (TSP) route, but depends on the variance of customer demands, and, if in-transit inventory-holding costs are charged, also on mean customer demands. We then examine dynamic-routing policies, i.e., policies that can change the route from one system-replenishment-allocation cycle to another, based on the status of the retailers’ inventories. Next, the performance of a change-revert heuristic policy is examined. Although its routing decisions are not fully dynamic, but determined and fixed for a given cycle at the time of each system replenishment, simulation tests with N = 2 and N = 6 retailers indicate that its use can substantially reduce system inventory-related costs even if most of the time the chosen route is the optimal static route. 4/16/2009
6. PROPOSED MODEL The model examined by the authors consists of a single cross-docking warehouse, N retailers, one un-capacitated vehicle, and a single item (SKU). This supply chain is centrally managed, using a periodic-review system. Each retailer i experiences normally distributed customer demand each time period. Demand realizations are independent across time and across retailers. Excess demand is backordered at cost $p/unit-period, and a holding cost of $h/unit-period is charged on system (i.e., on-vehicle or at-retailer) inventory. Transportation times between system sites are fixed and known. 4/16/2009
7. ASSUMPTIONS Three major assumptions are made to facilitate our Analysis. The Allocation Assumption The Returns-Without-Penalty-Assumption The Last-Period Backorders Assumption 4/16/2009
8. MODEL The total cost assigned to a single cycle that starts in period t0, and whose retailers’ allocation cycles have known arbitrary starting and ending periods, is 4/16/2009 where Et is the system total net inventory, si t are the backorders at retailer i in period t, and e[i ]is the end period in retailer i’s allocation cycle. H is the holding cost and p is the penalty for back-orders.
10. MODEL While Y ∗, K∗, µ1c and σ1c are identical under the two cost structures, 4/16/2009 Retailer-only holding costs: A sufficient condition to visit the closest retailer first is for the closest retailer to also have the largest variance. Otherwise, the choice of the optimal static route depends on a trade-off between travel times (i.e., a TSP-oriented parameter) and per-period demand variance (i.e., an inventory management parameter). System based holding costs: Hence, when holding costs are also charged on the vehicle inventory, the retailers’ average demands affect the choice of the route.
11. DYNAMIC ROUTING POLICIES Dynamic Routing introduces two types of uncertainties, neither of which is present under a fixed routing policy: (1) “UAL uncertainty,” i.e., uncertainty in each retailer’s delivery lead time, and (2) “UPD uncertainty,” i.e., uncertainty in the number of periods of customer demand each retailer’s allocation is to supply. A management decision to adopt a dynamic-routing policy should be viewed as a tradeoff between reducing expected inventory-related costs, in exchange for increased logistics-related (e.g., transportation) cost. In a symmetric system for any given inventory-allocation policy, least-inventory first (LIF) is an optimal dynamic routing policy. 4/16/2009
12. The heuristic’s decision rule is applied before the vehicle leaves the warehouse, and yields one of two decisions: (a) use the default route in the current replenishment cycle or (b) choose another route. The decision rule then chooses the route with the smallest value of C∗, where C* =Z* +(p+h)SP Where z* is the single-cycle cost Sp is the expected shortages of retailer in its last allocation cycle. 4/16/2009 CHANGE REVERT HEURISTIC
13. CONCLUSION The authors used simulation to examine the impact of the major assumptions used to develop the analytical model. The results indicate: that these assumptions are seldom violated; and, second, even when they are, the insights provided by the analytical model—in particular, the model’s estimates of cost/period and the desirability of changing routes—appear to be insensitive to them. In particular, the simulation results provide evidence that the change revert heuristic provides statistically significant and managerially meaningful savings for multi retailer systems. 4/16/2009
14. SCOPE FOR RESEARCH Finally, the authors deliberately leave two questions open for future research: First is an examination of fully dynamic-routing policy. This form of dynamic routing would decide which retailer to visit next as part of the allocation decision made at every retailer (except the last) in each replenishment cycle. Second is a closer examination of change-revert routing policies. Perhaps the most interesting question here is “What is the best default route?” We arbitrarily chose the optimal static route to be the default route, but, given a change-revert policy, it is certainly possible that a different default route would provide even better results. 4/16/2009