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Solving multi-objective dynamic vehicle routing problem with time windows using multi-objective algorithm

Logistics plays a very important role in the business economy. It is over a trillion of dollars in revenue annually and increase exponentially over the years One of the current trends is to solve the last mile is to optimize the delivery routes. One of the best ways to optimize the delivery routes i...

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Main Author: Khoo, Thau Soon
Format: Final Year Project / Dissertation / Thesis
Published: 2022
Subjects:
QA Mathematics
Online Access:http://eprints.utar.edu.my/4536/1/1308520_Khoo_Thau_Soon.pdf
http://eprints.utar.edu.my/4536/
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spelling my-utar-eprints.45362022-12-15T18:49:17Z Solving multi-objective dynamic vehicle routing problem with time windows using multi-objective algorithm Khoo, Thau Soon QA Mathematics Logistics plays a very important role in the business economy. It is over a trillion of dollars in revenue annually and increase exponentially over the years One of the current trends is to solve the last mile is to optimize the delivery routes. One of the best ways to optimize the delivery routes is to study and implement the multi-objective dynamic vehicle routing problem with time windows because it resembles the online delivery services that are ubiquitous and propagate over the year, especially during the COVID-19 pandemic. During the past decade, there is an increasing trend of published papers dealing with dynamic vehicle routing problems with time windows (DVRPTW) but not on multi-objective dynamic vehicle routing problems with time windows (MODVRPTW). Therefore, it brings a significant contribution if this study can be carried out because it represents the daily real-life problem in transportation. To solve this problem, it needs to be modelled and an algorithm is needed to be developed and tested to ascertain its efficiency and effectiveness. It is difficult and challenging to develop an algorithm that can produce consistent near-optimal solutions even after many runs, average near-optimal solutions that have the least difference in magnitude, broader Pareto set, and iii achieve near-optimal solutions but highly sought after if it is commercially viable. Our algorithm uses non-fitness evolutionary distributed parallelized adaptive large neighbourhood search (NEDPALNS). The non-fitness evolutionary distributed (NED) takes advantage of the exploitation of the search space and the parallelized adaptive large neighbourhood search (PALNS) makes full use of the exploration and exploitation of its inner strength. These combinations achieve near-optimal solutions consistently. We compare our results using hypothetical datasets and real datasets. Our results are competitive and outperform other published algorithms and best-known solutions in both static and dynamic environments. 2022 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/4536/1/1308520_Khoo_Thau_Soon.pdf Khoo, Thau Soon (2022) Solving multi-objective dynamic vehicle routing problem with time windows using multi-objective algorithm. PhD thesis, UTAR. http://eprints.utar.edu.my/4536/
institution Universiti Tunku Abdul Rahman
building UTAR Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tunku Abdul Rahman
content_source UTAR Institutional Repository
url_provider http://eprints.utar.edu.my
topic QA Mathematics
spellingShingle QA Mathematics
Khoo, Thau Soon
Solving multi-objective dynamic vehicle routing problem with time windows using multi-objective algorithm
description Logistics plays a very important role in the business economy. It is over a trillion of dollars in revenue annually and increase exponentially over the years One of the current trends is to solve the last mile is to optimize the delivery routes. One of the best ways to optimize the delivery routes is to study and implement the multi-objective dynamic vehicle routing problem with time windows because it resembles the online delivery services that are ubiquitous and propagate over the year, especially during the COVID-19 pandemic. During the past decade, there is an increasing trend of published papers dealing with dynamic vehicle routing problems with time windows (DVRPTW) but not on multi-objective dynamic vehicle routing problems with time windows (MODVRPTW). Therefore, it brings a significant contribution if this study can be carried out because it represents the daily real-life problem in transportation. To solve this problem, it needs to be modelled and an algorithm is needed to be developed and tested to ascertain its efficiency and effectiveness. It is difficult and challenging to develop an algorithm that can produce consistent near-optimal solutions even after many runs, average near-optimal solutions that have the least difference in magnitude, broader Pareto set, and iii achieve near-optimal solutions but highly sought after if it is commercially viable. Our algorithm uses non-fitness evolutionary distributed parallelized adaptive large neighbourhood search (NEDPALNS). The non-fitness evolutionary distributed (NED) takes advantage of the exploitation of the search space and the parallelized adaptive large neighbourhood search (PALNS) makes full use of the exploration and exploitation of its inner strength. These combinations achieve near-optimal solutions consistently. We compare our results using hypothetical datasets and real datasets. Our results are competitive and outperform other published algorithms and best-known solutions in both static and dynamic environments.
format Final Year Project / Dissertation / Thesis
author Khoo, Thau Soon
author_facet Khoo, Thau Soon
author_sort Khoo, Thau Soon
title Solving multi-objective dynamic vehicle routing problem with time windows using multi-objective algorithm
title_short Solving multi-objective dynamic vehicle routing problem with time windows using multi-objective algorithm
title_full Solving multi-objective dynamic vehicle routing problem with time windows using multi-objective algorithm
title_fullStr Solving multi-objective dynamic vehicle routing problem with time windows using multi-objective algorithm
title_full_unstemmed Solving multi-objective dynamic vehicle routing problem with time windows using multi-objective algorithm
title_sort solving multi-objective dynamic vehicle routing problem with time windows using multi-objective algorithm
publishDate 2022
url http://eprints.utar.edu.my/4536/1/1308520_Khoo_Thau_Soon.pdf
http://eprints.utar.edu.my/4536/
_version_ 1753792983561404416
score 13.211869

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