An artificial bee colony algorithm for the vehicle routing problem with backhauls and time windows

An artificial bee colony algorithm for the vehicle routing problem with backhauls and time windows

The vehicle routing problem with backhauls and time windows (VRPBTW) aims to find a feasible vehicle route that minimizes the total traveling distance while imposing capacity, backhaul, and time-window constraints. We present an enhanced artificial bee colony algorithm (EABCA), which is a meta-heu...

Full description

Bibliographic Details
Main Authors: Tanawat Worawattawechai, Boonyarit Intiyot, Chawalit Jeenanunta
Format: Article
Language:English
Published: Prince of Songkla University 2019-02-01
Series:Songklanakarin Journal of Science and Technology (SJST)
Subjects:
meta-heuristic
artificial bee colony
backhaul
time window
vehicle routing problems
Online Access:https://rdo.psu.ac.th/sjstweb/journal/41-1/18.pdf
id doaj-fbdae2dceedc45218a5043515f41faae
record_format Article
spelling doaj-fbdae2dceedc45218a5043515f41faae2020-11-24T21:26:40ZengPrince of Songkla UniversitySongklanakarin Journal of Science and Technology (SJST)0125-33952019-02-0141115115810.14456/sjst-psu.2019.18An artificial bee colony algorithm for the vehicle routing problem with backhauls and time windowsTanawat Worawattawechai0Boonyarit Intiyot1Chawalit Jeenanunta2Department of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University, Pathum Wan, Bangkok, 10330 ThailandDepartment of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University, Pathum Wan, Bangkok, 10330 ThailandSchool of Management Technology, Sirindhorn International Institute of Technology, Thammasat University, Khlong Luang, Pathum Thani, 12120 ThailandThe vehicle routing problem with backhauls and time windows (VRPBTW) aims to find a feasible vehicle route that minimizes the total traveling distance while imposing capacity, backhaul, and time-window constraints. We present an enhanced artificial bee colony algorithm (EABCA), which is a meta-heuristic, to solve this problem. Three strategies - a forbidden list, the sequential search for onlookers, and the combination of 1-move intra-route exchange and λ-interchange technique - are introduced for EABCA. The proposed method was tested on a set of benchmark instances. The computational results show that the EABCA can produce better solutions than the basic ABCA, and it discovered many new best-known solutions.https://rdo.psu.ac.th/sjstweb/journal/41-1/18.pdfmeta-heuristicartificial bee colonybackhaultime windowvehicle routing problems
collection DOAJ
language English
format Article
sources DOAJ
author Tanawat Worawattawechai
Boonyarit Intiyot
Chawalit Jeenanunta
spellingShingle Tanawat Worawattawechai
Boonyarit Intiyot
Chawalit Jeenanunta
An artificial bee colony algorithm for the vehicle routing problem with backhauls and time windows
Songklanakarin Journal of Science and Technology (SJST)
meta-heuristic
artificial bee colony
backhaul
time window
vehicle routing problems
author_facet Tanawat Worawattawechai
Boonyarit Intiyot
Chawalit Jeenanunta
author_sort Tanawat Worawattawechai
title An artificial bee colony algorithm for the vehicle routing problem with backhauls and time windows
title_short An artificial bee colony algorithm for the vehicle routing problem with backhauls and time windows
title_full An artificial bee colony algorithm for the vehicle routing problem with backhauls and time windows
title_fullStr An artificial bee colony algorithm for the vehicle routing problem with backhauls and time windows
title_full_unstemmed An artificial bee colony algorithm for the vehicle routing problem with backhauls and time windows
title_sort artificial bee colony algorithm for the vehicle routing problem with backhauls and time windows
publisher Prince of Songkla University
series Songklanakarin Journal of Science and Technology (SJST)
issn 0125-3395
publishDate 2019-02-01
description The vehicle routing problem with backhauls and time windows (VRPBTW) aims to find a feasible vehicle route that minimizes the total traveling distance while imposing capacity, backhaul, and time-window constraints. We present an enhanced artificial bee colony algorithm (EABCA), which is a meta-heuristic, to solve this problem. Three strategies - a forbidden list, the sequential search for onlookers, and the combination of 1-move intra-route exchange and λ-interchange technique - are introduced for EABCA. The proposed method was tested on a set of benchmark instances. The computational results show that the EABCA can produce better solutions than the basic ABCA, and it discovered many new best-known solutions.
topic meta-heuristic
artificial bee colony
backhaul
time window
vehicle routing problems
url https://rdo.psu.ac.th/sjstweb/journal/41-1/18.pdf
work_keys_str_mv AT tanawatworawattawechai anartificialbeecolonyalgorithmforthevehicleroutingproblemwithbackhaulsandtimewindows
AT boonyaritintiyot anartificialbeecolonyalgorithmforthevehicleroutingproblemwithbackhaulsandtimewindows
AT chawalitjeenanunta anartificialbeecolonyalgorithmforthevehicleroutingproblemwithbackhaulsandtimewindows
AT tanawatworawattawechai artificialbeecolonyalgorithmforthevehicleroutingproblemwithbackhaulsandtimewindows
AT boonyaritintiyot artificialbeecolonyalgorithmforthevehicleroutingproblemwithbackhaulsandtimewindows
AT chawalitjeenanunta artificialbeecolonyalgorithmforthevehicleroutingproblemwithbackhaulsandtimewindows
_version_ 1725978189351616512

Similar Items