Particle swarm optimization for just-in-time trucks scheduling in cross docking terminals

© IEOM Society International. In this paper, we present an application of Particle Swarm Optimization (PSO) for solving truck scheduling problem in a cross docking system in the content of just-in-time concept The objective is to find the schedule of inbound and outbound trucks that minimize the tot...

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Main Authors: Warisa Wisittipanich, Piya Hengmeechai
Format: Conference Proceeding
Published: 2018
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Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85018393600&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/55333
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-553332018-09-05T03:01:30Z Particle swarm optimization for just-in-time trucks scheduling in cross docking terminals Warisa Wisittipanich Piya Hengmeechai Business, Management and Accounting Decision Sciences Engineering © IEOM Society International. In this paper, we present an application of Particle Swarm Optimization (PSO) for solving truck scheduling problem in a cross docking system in the content of just-in-time concept The objective is to find the schedule of inbound and outbound trucks that minimize the total earliness and the total tardiness simultaneously. The mathematical model is first presented as a mixed integer programming (MIP) model and LINGO optimization solver is then used to find the optimal solution. Due to the limitation of LINGO to obtain only one single solution related to one objective at a time, it requires additional runs to get a solution in the other objective aspect. Moreover, when the problem size becomes very large, LINGO cannot find solutions in an acceptable time. Consequently, we apply a multi-objective particle swarm optimization (MOPSO) to find a set of truck schedules with minimum total earliness and total tardiness. The performances of MOPSO are evaluated using 20 generated instances and compared with those obtained from multi-objective Differential Evolution (MODE). The experimental results demonstrate that both MOPSO and MODE are capable of finding a set of diverse and high quality non-dominated solutions with reasonable computing time. © IEOM Society International. 2018-09-05T02:54:30Z 2018-09-05T02:54:30Z 2016-01-01 Conference Proceeding 21698767 2-s2.0-85018393600 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85018393600&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/55333
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
topic Business, Management and Accounting
Decision Sciences
Engineering
spellingShingle Business, Management and Accounting
Decision Sciences
Engineering
Warisa Wisittipanich
Piya Hengmeechai
Particle swarm optimization for just-in-time trucks scheduling in cross docking terminals
description © IEOM Society International. In this paper, we present an application of Particle Swarm Optimization (PSO) for solving truck scheduling problem in a cross docking system in the content of just-in-time concept The objective is to find the schedule of inbound and outbound trucks that minimize the total earliness and the total tardiness simultaneously. The mathematical model is first presented as a mixed integer programming (MIP) model and LINGO optimization solver is then used to find the optimal solution. Due to the limitation of LINGO to obtain only one single solution related to one objective at a time, it requires additional runs to get a solution in the other objective aspect. Moreover, when the problem size becomes very large, LINGO cannot find solutions in an acceptable time. Consequently, we apply a multi-objective particle swarm optimization (MOPSO) to find a set of truck schedules with minimum total earliness and total tardiness. The performances of MOPSO are evaluated using 20 generated instances and compared with those obtained from multi-objective Differential Evolution (MODE). The experimental results demonstrate that both MOPSO and MODE are capable of finding a set of diverse and high quality non-dominated solutions with reasonable computing time. © IEOM Society International.
format Conference Proceeding
author Warisa Wisittipanich
Piya Hengmeechai
author_facet Warisa Wisittipanich
Piya Hengmeechai
author_sort Warisa Wisittipanich
title Particle swarm optimization for just-in-time trucks scheduling in cross docking terminals
title_short Particle swarm optimization for just-in-time trucks scheduling in cross docking terminals
title_full Particle swarm optimization for just-in-time trucks scheduling in cross docking terminals
title_fullStr Particle swarm optimization for just-in-time trucks scheduling in cross docking terminals
title_full_unstemmed Particle swarm optimization for just-in-time trucks scheduling in cross docking terminals
title_sort particle swarm optimization for just-in-time trucks scheduling in cross docking terminals
publishDate 2018
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85018393600&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/55333
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