Technical report: genetic algorithm for solving capacitated vehicle routing problem / Mohd Faris Mohd Zaki and Muhammad Ammar Zulqornain Abdul Rashid

The capacitated vehicle routing problem (CVRP) is one of the most important problems in the optimization of distribution networks. The main objective for Capacitated Vehicle Routing Problem (CVRP) is to deliver goods to a set of customer with known demands through min­imum vehicle distance routes, s...

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Main Authors: Mohd Zaki, Mohd Faris, Abdul Rashid, Muhammad Ammar Zulqornain
Format: Student Project
Language:English
Published: 2017
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Online Access:https://ir.uitm.edu.my/id/eprint/109757/1/109757.pdf
https://ir.uitm.edu.my/id/eprint/109757/
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spelling my.uitm.ir.1097572025-02-11T08:40:38Z https://ir.uitm.edu.my/id/eprint/109757/ Technical report: genetic algorithm for solving capacitated vehicle routing problem / Mohd Faris Mohd Zaki and Muhammad Ammar Zulqornain Abdul Rashid Mohd Zaki, Mohd Faris Abdul Rashid, Muhammad Ammar Zulqornain Study and teaching Sequences (Mathematics) Analysis The capacitated vehicle routing problem (CVRP) is one of the most important problems in the optimization of distribution networks. The main objective for Capacitated Vehicle Routing Problem (CVRP) is to deliver goods to a set of customer with known demands through min­imum vehicle distance routes, starting and ending with the same depot and carrying limited capacity of the goods. Since it is difficult to solve this problem directly, we used Genetic Al­gorithm for Capacitated Vehicle Routing Problem (CVRP) as to get the optimized route with minimum distance travel without exceeding capacity constraint. The outcomes of GA achieve better result. There are several step in methodology which input data by using operator selection and randomly choose two routes. From the data, we conduct iteration process which consist of crossover, selection and mutation process. Based on the study, we believe that minimum distance for P is 396.66 and the selected order routes is 1-14-2-4-5-8-7-6-16-19-1-12-11-15-3- 13-9-17-18-10-l. The capacity carried for route 1 is 150 and route 2 is 160. While minimum distance for Q is 397.47 and the selected order routes is 1-2-5-3-4-15-7-8-9-19-1-11-12-13- 14-6-16-17-18-10-1. The capacity carried for route 1 and 2 are 159 and 151. Both capacity were valid since it does not exceed our capacity decision which the vehicle cannot carry more than 160. The result that are encoded in Matlab, we found that the best order of the route is 1-5-13-17-4-18-9-12-11-15-1-19-8-3-14-10-6-16-7-2-1 which distance travel is 294.52 and the capacity for route 1 and 2 are 151 and 159 From the result, It can be conclude that GA method can be apply to large city routes. 2017 Student Project NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/109757/1/109757.pdf Technical report: genetic algorithm for solving capacitated vehicle routing problem / Mohd Faris Mohd Zaki and Muhammad Ammar Zulqornain Abdul Rashid. (2017) [Student Project] <http://terminalib.uitm.edu.my/109757.pdf> (Unpublished)
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Study and teaching
Sequences (Mathematics)
Analysis
spellingShingle Study and teaching
Sequences (Mathematics)
Analysis
Mohd Zaki, Mohd Faris
Abdul Rashid, Muhammad Ammar Zulqornain
Technical report: genetic algorithm for solving capacitated vehicle routing problem / Mohd Faris Mohd Zaki and Muhammad Ammar Zulqornain Abdul Rashid
description The capacitated vehicle routing problem (CVRP) is one of the most important problems in the optimization of distribution networks. The main objective for Capacitated Vehicle Routing Problem (CVRP) is to deliver goods to a set of customer with known demands through min­imum vehicle distance routes, starting and ending with the same depot and carrying limited capacity of the goods. Since it is difficult to solve this problem directly, we used Genetic Al­gorithm for Capacitated Vehicle Routing Problem (CVRP) as to get the optimized route with minimum distance travel without exceeding capacity constraint. The outcomes of GA achieve better result. There are several step in methodology which input data by using operator selection and randomly choose two routes. From the data, we conduct iteration process which consist of crossover, selection and mutation process. Based on the study, we believe that minimum distance for P is 396.66 and the selected order routes is 1-14-2-4-5-8-7-6-16-19-1-12-11-15-3- 13-9-17-18-10-l. The capacity carried for route 1 is 150 and route 2 is 160. While minimum distance for Q is 397.47 and the selected order routes is 1-2-5-3-4-15-7-8-9-19-1-11-12-13- 14-6-16-17-18-10-1. The capacity carried for route 1 and 2 are 159 and 151. Both capacity were valid since it does not exceed our capacity decision which the vehicle cannot carry more than 160. The result that are encoded in Matlab, we found that the best order of the route is 1-5-13-17-4-18-9-12-11-15-1-19-8-3-14-10-6-16-7-2-1 which distance travel is 294.52 and the capacity for route 1 and 2 are 151 and 159 From the result, It can be conclude that GA method can be apply to large city routes.
format Student Project
author Mohd Zaki, Mohd Faris
Abdul Rashid, Muhammad Ammar Zulqornain
author_facet Mohd Zaki, Mohd Faris
Abdul Rashid, Muhammad Ammar Zulqornain
author_sort Mohd Zaki, Mohd Faris
title Technical report: genetic algorithm for solving capacitated vehicle routing problem / Mohd Faris Mohd Zaki and Muhammad Ammar Zulqornain Abdul Rashid
title_short Technical report: genetic algorithm for solving capacitated vehicle routing problem / Mohd Faris Mohd Zaki and Muhammad Ammar Zulqornain Abdul Rashid
title_full Technical report: genetic algorithm for solving capacitated vehicle routing problem / Mohd Faris Mohd Zaki and Muhammad Ammar Zulqornain Abdul Rashid
title_fullStr Technical report: genetic algorithm for solving capacitated vehicle routing problem / Mohd Faris Mohd Zaki and Muhammad Ammar Zulqornain Abdul Rashid
title_full_unstemmed Technical report: genetic algorithm for solving capacitated vehicle routing problem / Mohd Faris Mohd Zaki and Muhammad Ammar Zulqornain Abdul Rashid
title_sort technical report: genetic algorithm for solving capacitated vehicle routing problem / mohd faris mohd zaki and muhammad ammar zulqornain abdul rashid
publishDate 2017
url https://ir.uitm.edu.my/id/eprint/109757/1/109757.pdf
https://ir.uitm.edu.my/id/eprint/109757/
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