Route optimization algorithms are the mathematical formulas that solve vehicle routing problems.
Some Types of Routing:
1) Vehicle Route Problem (VRP)
2) Traveling Salesman Problem (TSP)
3) Ant Colony Optimization (ACO)
Route optimization algorithm are the mathematical formula that solve routing problems..
Some types of routing:
1) Vehicle Routing Problem (VRP)
2) Traveling Salesman Problem (TSP)
3) Ant Colony Optimization (ACO)
International Refereed Journal of Engineering and Science (IRJES)irjes
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International Refereed Journal of Engineering and Science (IRJES) is a leading international journal for publication of new ideas, the state of the art research results and fundamental advances in all aspects of Engineering and Science. IRJES is a open access, peer reviewed international journal with a primary objective to provide the academic community and industry for the submission of half of original research and applications
Application of Cumulative Axle Model To Impute Missing Traffic Data in Defect...IJERDJOURNAL
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Abstract: An automatic vehicle classification (AVC) station is typically composed of three sensors per lane. Instances of data missing from the traffic datasets collected at such stations can occur as a result of issues such as one of the sensors malfunctioning. Although various data imputation methods, such as autoregressive integrated moving average (ARIMA), exponential smoothing, and interpolation, have been proposed to deal with this problem, they are either too complicated or have significant errors. This paper proposes a model, called the âcumulative axle model,â that minimizes such errors in traffic volume data resulting from a malfunctioning sensor at AVC stations. Evaluations conducted in which missing traffic volume data imputation was simulated using the proposed cumulative axle model indicate that our method has a mean absolute percentage error (MAPE) of 2.92%. This is significantly more accurate than that of conventional imputation methods, which achieve a MAPE of only 10% on average.
In this presentation, a new routing model was introduced in the form of integer linear programming by combining the concepts of time windows and multiple demands and by considering the two contradictory goals of minimizing travel: cost and maximizing demand coverage.
Evaluation of level of service at chatikara, MathuraSHASHANK KAMAL
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Evaluation of level of service. Level of service (LOS) is a qualitative measure used to relate the quality of traffic service. LOS is used to analyze highways by categorizing traffic flow and assigning quality levels of traffic based on performance measure like speed, density,etc.
Route optimization algorithm are the mathematical formula that solve routing problems..
Some types of routing:
1) Vehicle Routing Problem (VRP)
2) Traveling Salesman Problem (TSP)
3) Ant Colony Optimization (ACO)
International Refereed Journal of Engineering and Science (IRJES)irjes
Â
International Refereed Journal of Engineering and Science (IRJES) is a leading international journal for publication of new ideas, the state of the art research results and fundamental advances in all aspects of Engineering and Science. IRJES is a open access, peer reviewed international journal with a primary objective to provide the academic community and industry for the submission of half of original research and applications
Application of Cumulative Axle Model To Impute Missing Traffic Data in Defect...IJERDJOURNAL
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Abstract: An automatic vehicle classification (AVC) station is typically composed of three sensors per lane. Instances of data missing from the traffic datasets collected at such stations can occur as a result of issues such as one of the sensors malfunctioning. Although various data imputation methods, such as autoregressive integrated moving average (ARIMA), exponential smoothing, and interpolation, have been proposed to deal with this problem, they are either too complicated or have significant errors. This paper proposes a model, called the âcumulative axle model,â that minimizes such errors in traffic volume data resulting from a malfunctioning sensor at AVC stations. Evaluations conducted in which missing traffic volume data imputation was simulated using the proposed cumulative axle model indicate that our method has a mean absolute percentage error (MAPE) of 2.92%. This is significantly more accurate than that of conventional imputation methods, which achieve a MAPE of only 10% on average.
In this presentation, a new routing model was introduced in the form of integer linear programming by combining the concepts of time windows and multiple demands and by considering the two contradictory goals of minimizing travel: cost and maximizing demand coverage.
Evaluation of level of service at chatikara, MathuraSHASHANK KAMAL
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Evaluation of level of service. Level of service (LOS) is a qualitative measure used to relate the quality of traffic service. LOS is used to analyze highways by categorizing traffic flow and assigning quality levels of traffic based on performance measure like speed, density,etc.
Presentation delivered at the 2015 Transportation Association of Canada (TAC) Conference & Exhibition, from September 27 to 30, during the session entitled Goods Movement - Reaching Destinations Safely and Efficiently.
Prepared by
François BÊlisle, Eng., B. Sc., M.A.
Marilyne Brosseau, Eng., M.Eng.
Steve Careau, Eng.
Philippe Mytofir, techn.
Validated by:
Stephan Kellner, Eng., M.Eng.
Detailed description of Capacity and Level of service of Multi lane highways based on Highway Capacity Manual (HCM2010) along with one example for finding LOS of a highway
Transit Signalisation Priority (TSP) - A New Approach to Calculate GainsWSP
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Presentation by François BÊlisle, Eng. , B.Sc., M.A. and Stephan Kellner, Eng., P.Eng., MS delivered at the 2015 Transportation Association of Canada (TAC) Conference & Exhibition, from September 27 to 30.
Slides of the article "CTPATH: A Real World System to Enable Green Transportation by Optimizing Environmentally Friendly Routing Paths" for the congress Smart-CT, MÃĄlaga (Spain), June 2016
A Transportation Problem is
one of the
most
typical
problems being encountered in many situations
and
it
has
many
practical applic
ations. Many researches had been conducted
and
many methods
had been proposed to solve it. One of the most
difficult challenge in solving the problem deals with inputting a
very large volume of data. With the development of intelligent
technologies, compu
ters had already been used to solved this
problem. This paper presents a method using Genetic Algorithm
(GA) t
o provide a new tool that can quickly calculate the solution
to the Balanced Transportation Problem.
The test results are compared with selected o
ld methods to
confirm the effectiveness of the use of GA. A
mathematical model
was used to represent the GA and be applied to solve it. Finally,
the test results of the model were presented so show the
effectiveness.
Optimization Approach for Capacitated Vehicle Routing Problem Using Genetic A...ijsrd.com
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Vehicle Routing Problem (VRP) is a combinatorial optimization problem which deals with fleet of vehicles to serve n number of customers from a central depot. Each customer has a certain demand that must be satisfied using each vehicle that has the same capacity (homogeneous fleet). Each customer is served by a particular vehicle in such a way that the same customer is not served by another vehicle. In this paper, Genetic Algorithm (GA) is used to get the optimized vehicle route with minimum distance for Capacitated Vehicle Routing Problem (CVRP). The outcomes of GA achieve better optimization and gives good performance. Further, GA is enhanced to minimize the number of vehicles.
The Optimizing Multiple Travelling Salesman Problem Using Genetic Algorithmijsrd.com
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The traveling salesman problem (TSP) supports the idea of a single salesperson traveling in a continuous trip visiting all n cities exactly once and returning to the starting point. The multiple traveling salesman problems (mTSP) is complex combinatorial optimization problem, which is a generalization of the well-known Travelling Salesman Problem (TSP), where one or more salesman can be used in the path. In this paper mTSP has also been studied and solved with GA in the form of the vehicle scheduling problem. The existing model is new models are compared to both mathematically and experimentally. This work presents a chromosome methodology setting up the MTSP to be solved using a GA.
Class GA. Genetic Algorithm,Genetic Algorithmraed albadri
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Genetic Algorithms are good at taking large, potentially huge search spaces and navigating them, looking for optimal combinations of things, solutions you might not otherwise find in a lifetime
Genetic Algorithm
Presentation delivered at the 2015 Transportation Association of Canada (TAC) Conference & Exhibition, from September 27 to 30, during the session entitled Goods Movement - Reaching Destinations Safely and Efficiently.
Prepared by
François BÊlisle, Eng., B. Sc., M.A.
Marilyne Brosseau, Eng., M.Eng.
Steve Careau, Eng.
Philippe Mytofir, techn.
Validated by:
Stephan Kellner, Eng., M.Eng.
Detailed description of Capacity and Level of service of Multi lane highways based on Highway Capacity Manual (HCM2010) along with one example for finding LOS of a highway
Transit Signalisation Priority (TSP) - A New Approach to Calculate GainsWSP
Â
Presentation by François BÊlisle, Eng. , B.Sc., M.A. and Stephan Kellner, Eng., P.Eng., MS delivered at the 2015 Transportation Association of Canada (TAC) Conference & Exhibition, from September 27 to 30.
Slides of the article "CTPATH: A Real World System to Enable Green Transportation by Optimizing Environmentally Friendly Routing Paths" for the congress Smart-CT, MÃĄlaga (Spain), June 2016
A Transportation Problem is
one of the
most
typical
problems being encountered in many situations
and
it
has
many
practical applic
ations. Many researches had been conducted
and
many methods
had been proposed to solve it. One of the most
difficult challenge in solving the problem deals with inputting a
very large volume of data. With the development of intelligent
technologies, compu
ters had already been used to solved this
problem. This paper presents a method using Genetic Algorithm
(GA) t
o provide a new tool that can quickly calculate the solution
to the Balanced Transportation Problem.
The test results are compared with selected o
ld methods to
confirm the effectiveness of the use of GA. A
mathematical model
was used to represent the GA and be applied to solve it. Finally,
the test results of the model were presented so show the
effectiveness.
Optimization Approach for Capacitated Vehicle Routing Problem Using Genetic A...ijsrd.com
Â
Vehicle Routing Problem (VRP) is a combinatorial optimization problem which deals with fleet of vehicles to serve n number of customers from a central depot. Each customer has a certain demand that must be satisfied using each vehicle that has the same capacity (homogeneous fleet). Each customer is served by a particular vehicle in such a way that the same customer is not served by another vehicle. In this paper, Genetic Algorithm (GA) is used to get the optimized vehicle route with minimum distance for Capacitated Vehicle Routing Problem (CVRP). The outcomes of GA achieve better optimization and gives good performance. Further, GA is enhanced to minimize the number of vehicles.
The Optimizing Multiple Travelling Salesman Problem Using Genetic Algorithmijsrd.com
Â
The traveling salesman problem (TSP) supports the idea of a single salesperson traveling in a continuous trip visiting all n cities exactly once and returning to the starting point. The multiple traveling salesman problems (mTSP) is complex combinatorial optimization problem, which is a generalization of the well-known Travelling Salesman Problem (TSP), where one or more salesman can be used in the path. In this paper mTSP has also been studied and solved with GA in the form of the vehicle scheduling problem. The existing model is new models are compared to both mathematically and experimentally. This work presents a chromosome methodology setting up the MTSP to be solved using a GA.
Class GA. Genetic Algorithm,Genetic Algorithmraed albadri
Â
Genetic Algorithms are good at taking large, potentially huge search spaces and navigating them, looking for optimal combinations of things, solutions you might not otherwise find in a lifetime
Genetic Algorithm
This presentation is intended for giving an introduction to Genetic Algorithm. Using an example, it explains the different concepts used in Genetic Algorithm. If you are new to GA or want to refresh concepts , then it is a good resource for you.
A New Paradigm in User Equilibrium-Application in Managed Lane PricingCSCJournals
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Ineffective use of the High-Occupancy-Vehicle (HOV) lanes has the potential to decrease the overall roadway throughput during peak periods. Excess capacity in HOV lanes during peak periods can be made available to other types of vehicles, including single occupancy vehicles (SOV) for a price (toll). Such dual use lanes are known as âManaged Lanes.â The main purpose of this research is to propose a new paradigm in user equilibrium to predict the travel demand for determining the optimal fare policy for managed lane facilities. Depending on their value of time, motorists may choose to travel on Managed Lanes (ML) or General Purpose Lanes (GPL). In this study, the features in the software called Toll Pricing Modeler version 4.3 (TPM-4.3) are described. TPM-4.3 is developed based on this new user equilibrium concept and utilizes it to examine various operating scenarios. The software has two built-in operating objective options: 1) what would the ML operating speed be for a specified SOV toll, or 2) what should the SOV toll be for a desired minimum ML operating speed. A number of pricing policy scenarios are developed and examined on the proposed managed lane segment on Interstate 30 (I-30) in Grand Prairie, Texas. The software provides quantitative estimates of various factors including toll revenue, emissions and system performance such as person movement and traffic speed on managed and general purpose lanes. Overall, among the scenarios examined, higher toll rates tend to generate higher toll revenues, reduce overall CO and NOx emissions, and shift demand to general purpose lanes. On the other hand, HOV preferential treatments at any given toll level tend to reduce toll revenue, have no impact on or reduce system performance on managed lanes, and increase CO and NOx emissions.
(Paper) Parking Navigation for Alleviating Congestion in Multilevel Parking F...Naoki Shibata
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Kenmotsu, M., Sun, W., Shibata, N., Yasumoto, K. and Ito, M. : "Parking Navigation for Alleviating Congestion in Multilevel Parking Facility," Proc. of 2012 IEEE 76th Vehicular Technology Conference (VTC2012-Fall), Sep.2012.
Abstract - Finding a vacant parking space in a large crowded parking facility takes long time. In this paper, we propose a navigation method that minimizes the parking time based on collected real-time positional information of cars. In the proposed method, a central server in the parking facility collects the information and estimates the occupancy of each parking zone. Then, the server broadcasts the occupancy data to the cars in the parking facility. Each car then computes a parking route with the shortest expected parking waiting time and shows it to the driver. We conducted simulation-based evaluations of the proposed method using a realistic model based on trace data taken from a real parking facility. We confirmed that the proposed method reduced parking waiting time by 20%â70% even with low system penetration.
Operatioal analysis of any road is necessary for its design,planning and implementation procedure.This article mostly deals with preliminary proposal of two lane road of eastern region of Nepal.due to increased traffic condition servicabilty and level of service of koshi higway is found to be very poor hence Dharan submetropolitan city's part is analysed.
Replacing Manhattan Subway Service with On-demand transportationChristian Moscardi
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The NYC subway is in dire need of repairs. We propose a station-to-station on-demand transit model where users would dial to request pickup/drop-off at subway stations on Manhattan.
This would allow the subway on Manhattan to shut down from 12AM-5AM, facilitating speedy repairs.
Seeking to quantify the viability of operating microtransit shuttles from station to station during nighttime (and weekend) subway closures that the MTA will take to support their signal upgrades.
JAVA 2013 IEEE DATAMINING PROJECT T drive enhancing driving directions with t...IEEEGLOBALSOFTTECHNOLOGIES
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To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
T drive enhancing driving directions with taxi driversâ intelligenceIEEEFINALYEARPROJECTS
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To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.coÂŦm-Visit Our Website: www.finalyearprojects.org
Viamente offers turnkey solutions for the veichle routing based on its own proprietary Routing Optimization and Scheduling Engine. Viamente keeps investing in maths and cloud computing with the final goal to support a green economy of mobility.
An Enhanced Agglomerative Clustering Algorithm for Solving Vehicle Routing Pr...ijtsrd
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An aggrandized solution is designed for the vehicles to reduce the total cost of distribution by which it can supply the goods to the customers with its known capacity can be named as a vehicle routing problem. In variable neighborhood search method, mainly an efficient vehicle routing can be achieved by calculating the distance matrix value based on the customers location or the path where the customers resides. The main objective of the paper is to reduce the total distance travelled to deliver the goods to the customers. The proposed algorithm is a hierarchy based enhanced agglomerative clustering algorithm technique which is used in the data mining scenario effectively. The proposed algorithm decreases the total distance assigning to each route and the important thing need to consider is that, this enhanced clustering algorithm can reduce the total distance when compared to the previously proposed variable neighborhood search method. V. Praveen | V. Hemalatha | M. Poovizhi"An Enhanced Agglomerative Clustering Algorithm for Solving Vehicle Routing Problem" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-6 , October 2017, URL: http://www.ijtsrd.com/papers/ijtsrd4701.pdf http://www.ijtsrd.com/computer-science/other/4701/an-enhanced-agglomerative-clustering-algorithm-for-solving-vehicle-routing-problem/v-praveen
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
A Strategic Approach: GenAI in EducationPeter Windle
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Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
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Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
The simplified electron and muon model, Oscillating Spacetime: The Foundation...RitikBhardwaj56
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Discover the Simplified Electron and Muon Model: A New Wave-Based Approach to Understanding Particles delves into a groundbreaking theory that presents electrons and muons as rotating soliton waves within oscillating spacetime. Geared towards students, researchers, and science buffs, this book breaks down complex ideas into simple explanations. It covers topics such as electron waves, temporal dynamics, and the implications of this model on particle physics. With clear illustrations and easy-to-follow explanations, readers will gain a new outlook on the universe's fundamental nature.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
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http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasnât one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
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Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
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This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
5. Some Types of Routing
ī Vehicle Routing Problem (VRP)
ī Travelling Salesman Problem (TSP)
ī Ant Colony Optimization (ACO)
1/12/2016 5
6. INTRODUCTION
Routing optimization Algorithms basically designs for
the best routes to reduce travel cost, energy
consumption and time. Due to non-deterministic
polynomial-time hard complexity, many route
optimizations involved in real-world applications
require too much computing effort. Shortening
computing time for Routing optimization is a great
challenge for state-of-the-art local optimization
algorithms.
1/12/2016 6
7. Logistic Model
The applications of vehicle routing problem (VRP) are
very common in real life. It can be described by the
scenario that follows. Let consider a depot having a
fleet of vehicles with limited capacities and a set of
customers, each with a certain demand for the
merchandise or goods to be dispatched. The problem
is to determine optimal routings for each vehicle to
visit every customer exactly once in order to fulfill the
demand. The most common goal for optimization is to
minimize the overall distance travelled by the vehicles.
1/12/2016 7
8. Logistic Model
The vehicle routing problem has been one of the
elementary problems in logistics ever since because of its
wide use. Vehicle Routing Problem (VRP) can be described
as follows. Suppose there are M vehicles each of which has
a capacity of Q and N customers who must be served from
a certain depot(terminal station). The goods each customer
asks for and the distance between them are known in
advance. The vehicles start from the depot(terminal
station), supply the customers and go back to the depot. It
is required that the route of the vehicles should be
arranged appropriately so that the least number of vehicles
is used and the shortest distance is covered.
1/12/2016 8
9. Conditions
The following conditions must be satisfied:
īThe total demand of any vehicle route must not exceed
the capacity of the vehicle.
īAny given customer is served by one, and only one
vehicle.
īCustomer delivery should be done efficiently and
economically.
1/12/2016 9
11. Proposed Methodologies
The methodologies used to determine the best vehicle
routing for truck dispatch system (TDS) are
īPermutation Enumerator
īGreedy Search Algorithm
1/12/2016 11
12. Permutation Enumerator
Initially the distance of the stations are considered as
known factors along with the capacity of the vehicles
used. Each vehicle is assigned to a set of stations based
upon the demand and capacity of the vehicles. First by
means of permutations and combinations possible set
of routes for each vehicles are formed. Among the
route combinations best routes are formed based upon
the distance i.e. based on shortest distances. This
method is suitable for least no of stations (n< 5).
1/12/2016 12
13. Greedy Search Algorithm
A âgreedy algorithmâ firstly, based on the list of nodes that
a truck is assigned to service, it starts the sequence by
choosing from the list a station that is nearest to the
terminal station. Then the next station in the sequence is
determined by choosing the station that is nearest to the
preceding station from the list of remaining stations. This
process is repeated, until all the stations have been
exhausted to form the complete sequence starting and
ending at the terminal station by knowing the distances to
be travelled by the vehicles using genetic algorithm an
optimized routing plan is formed for each set of vehicles.
This will help to reach the customers in both effective and
efficient manner.
1/12/2016 13
15. Shortest Route Calculations for
the Stations
īFor vehicle routing of truck dispatch system, finding a
shortest route.
ī8 stations including depot and no of vehicles used is
independent.
īCondition chosen is 3 stations can be visited by a
vehicle at a time.
īThe no of stations and the no of visits by a vehicle can
be altered according to the conditions.
1/12/2016 15
16. Shortest Route Calculations for
the Stations
First by means of permutations the total no of
combinations for shortest path is found.
Permutation Formula:
nCr = n!/r! (n-r)!
The no of all combinations of ânâ things, taken ârâ at a time
By combination
The total no of stations = 7
No of vehicle = 3
Hence, by formula
nCr = 7C3= 35 combinations
The total no of stations and stations that a vehicle can visit
can be altered according to situation.
1/12/2016 16
18. Advantages :
ī Improved Methodology of Additional terminals
generation :
Stop of which service capacity in rush hours falls
between standard and can be taken as potential
terminal. In other words, a terrific signal stop system
can be potential terminal if its number of vehicles in
rush hours fall between 100 and 400.
ī Competition caused by Parallel routes and rail
route
It considers the number of shared stops or
overlapping length between bus routes and rail routes.
However, in real situations, competition caused by the
parallel routes is inevitable.
1/12/2016 18
19. Disadvantages:
ī More detailed flow analysis should be carried out at stop
level.
At the present, passenger flow analysis is mainly implemented at
the route level. If the passenger attraction can be dis-aggregated
to each top on the route so analysis will become un-accurate.
ī All the Optimized vehicles routes should be evaluated and
compared.
Due to limitation of research time, evaluation after
optimization is only carried out in some important areas such as
commercial and residential zones at the individual route level.
So the distributed optimization for vehicles along with flow
analysis of passengers is not particularly considered.
1/12/2016 19
21. Conclusions and Future Work
Vehicle routing is first initiated with number of
stations to be served and total no of vehicles employed
to serve the stations based upon permutations and
combinations. Based on permutation and
combinations routings were formed. In case of large
number of vehicles greedy search method is used to
find the distances between the stations and the vehicle
routes distances. Here vehicle routing has been done
based upon known demand and capacity of the
suppliers.
1/12/2016 21