Multidirection Update-Based Multiobjective Particle Swarm Optimization for Mixed No-Idle Flow-Shop Scheduling Problem

The Mixed No-Idle Flow-shop Scheduling Problem (MNIFSP) is an extension of flow-shop scheduling, which has practical significance and application prospects in production scheduling. To improve the efficacy of solving the complicated multiobjective MNIFSP, a MultiDirection Update (MDU) based Multiobj...

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Published in:Complex System Modeling and Simulation Vol. 1; no. 3; pp. 176 - 197
Main Authors: Zhang, Wenqiang, Hou, Wenlin, Li, Chen, Yang, Weidong, Gen, Mitsuo
Format: Journal Article
Language:English
Published: Tsinghua University Press 01.09.2021
Subjects:
mixed no-idle flow-shop scheduling problem (mnlfsp)
multidirection update
multiobjective optimization
particle swarm optimization (pso)
ISSN:2096-9929, 2096-9929
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Abstract The Mixed No-Idle Flow-shop Scheduling Problem (MNIFSP) is an extension of flow-shop scheduling, which has practical significance and application prospects in production scheduling. To improve the efficacy of solving the complicated multiobjective MNIFSP, a MultiDirection Update (MDU) based Multiobjective Particle Swarm Optimization (MDU-MoPSO) is proposed in this study. For the biobjective optimization problem of the MNIFSP with minimization of makespan and total processing time, the MDU strategy divides particles into three subgroups according to a hybrid selection mechanism. Each subgroup prefers one convergence direction. Two subgroups are individually close to the two edge areas of the Pareto Front (PF) and serve two objectives, whereas the other one approaches the central area of the PF, preferring the two objectives at the same time. The MDU-MoPSO adopts a job sequence representation method and an exchange sequence-based particle update operation, which can better reflect the characteristics of sequence differences among particles. The MDU-MoPSO updates the particle in multiple directions and interacts in each direction, which speeds up the convergence while maintaining a good distribution performance. The experimental results and comparison of six classical evolutionary algorithms for various benchmark problems demonstrate the effectiveness of the proposed algorithm.
AbstractList The Mixed No-Idle Flow-shop Scheduling Problem (MNIFSP) is an extension of flow-shop scheduling, which has practical significance and application prospects in production scheduling. To improve the efficacy of solving the complicated multiobjective MNIFSP, a MultiDirection Update (MDU) based Multiobjective Particle Swarm Optimization (MDU-MoPSO) is proposed in this study. For the biobjective optimization problem of the MNIFSP with minimization of makespan and total processing time, the MDU strategy divides particles into three subgroups according to a hybrid selection mechanism. Each subgroup prefers one convergence direction. Two subgroups are individually close to the two edge areas of the Pareto Front (PF) and serve two objectives, whereas the other one approaches the central area of the PF, preferring the two objectives at the same time. The MDU-MoPSO adopts a job sequence representation method and an exchange sequence-based particle update operation, which can better reflect the characteristics of sequence differences among particles. The MDU-MoPSO updates the particle in multiple directions and interacts in each direction, which speeds up the convergence while maintaining a good distribution performance. The experimental results and comparison of six classical evolutionary algorithms for various benchmark problems demonstrate the effectiveness of the proposed algorithm.
Author Li, Chen
Zhang, Wenqiang
Gen, Mitsuo
Hou, Wenlin
Yang, Weidong
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Cites_doi 10.1016/j.ins.2020.01.018
10.1109/TEVC.2007.896686
10.1016/j.eswa.2019.01.057
10.1016/j.jcde.2016.05.001
10.1109/TEVC.2004.826067
10.1109/CEC.2002.1004388
10.1016/j.asoc.2017.01.017
10.1016/j.cor.2018.02.003
10.1016/j.cor.2011.10.024
10.1016/j.omega.2013.10.002
10.1016/j.swevo.2020.100689
10.1080/00207543.2018.1457812
10.1016/j.cie.2019.03.019
10.1007/s10845-013-0814-2
10.1162/EVCO_a_00104
10.1016/j.eswa.2019.113151
10.1007/s10845-015-1158-x
10.1016/j.swevo.2019.100557
10.1007/s00170-007-1252-0
10.1109/TEVC.2007.892759
10.1109/4235.996017
10.1109/MHS.1995.494215
10.3929/ethz-a-004284029
10.1080/0305215X.2018.1444163
10.1016/j.eswa.2019.113166
10.1007/s00521-015-2073-y
10.3390/a10040121
10.1109/TSMCB.2012.2209115
10.1002/nav.3800010110
10.1287/moor.1.2.117
10.1016/j.cor.2019.104839
10.1007/s10951-020-00637-8
10.1080/01605682.2019.1671149
10.1016/j.cie.2017.06.025
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References ref35
ref13
ref34
ref12
ref37
ref15
ref36
ref14
ref31
ref30
ref33
ref32
ref10
ref2
ref1
ref17
ref16
ref19
ref18
ref24
ref23
ref26
ref25
ref20
jiao (ref29) 2017; 15
ref22
ref21
ref28
schaffer (ref11) 1985
ref8
ref7
ref9
ref4
nouha (ref27) 2015
ref3
ref6
ref5
References_xml – ident: ref32
  doi: 10.1016/j.ins.2020.01.018
– ident: ref6
  doi: 10.1109/TEVC.2007.896686
– ident: ref14
  doi: 10.1016/j.eswa.2019.01.057
– ident: ref28
  doi: 10.1016/j.jcde.2016.05.001
– volume: 15
  start-page: 46
  year: 2017
  ident: ref29
  article-title: A niche sharing scheme-based coevolutionary particle swarm optimization algorithm for flow shop scheduling problem
  publication-title: Syst Cybern Inf
– ident: ref8
  doi: 10.1109/TEVC.2004.826067
– ident: ref7
  doi: 10.1109/CEC.2002.1004388
– ident: ref21
  doi: 10.1016/j.asoc.2017.01.017
– ident: ref22
  doi: 10.1016/j.cor.2018.02.003
– ident: ref20
  doi: 10.1016/j.cor.2011.10.024
– ident: ref2
  doi: 10.1016/j.omega.2013.10.002
– start-page: 93
  year: 1985
  ident: ref11
  article-title: Multiple objective optimization with vector evaluated genetic algorithms
  publication-title: Proc 1st Int Conf Genetic Algorithms
– ident: ref16
  doi: 10.1016/j.swevo.2020.100689
– ident: ref4
  doi: 10.1080/00207543.2018.1457812
– ident: ref37
  doi: 10.1016/j.cie.2019.03.019
– ident: ref12
  doi: 10.1007/s10845-013-0814-2
– ident: ref10
  doi: 10.1162/EVCO_a_00104
– ident: ref33
  doi: 10.1016/j.eswa.2019.113151
– ident: ref30
  doi: 10.1007/s10845-015-1158-x
– start-page: 145
  year: 2015
  ident: ref27
  article-title: A particle swarm optimization metaheuristic for the blocking flow shop scheduling problem: Total tardiness minimization
  publication-title: Proc of 13th European Conf EUMAS 2015 and Third Int Conf Multi-Agent Systems and Agreement Technologies
– ident: ref23
  doi: 10.1016/j.swevo.2019.100557
– ident: ref25
  doi: 10.1007/s00170-007-1252-0
– ident: ref36
  doi: 10.1109/TEVC.2007.892759
– ident: ref34
  doi: 10.1109/4235.996017
– ident: ref5
  doi: 10.1109/MHS.1995.494215
– ident: ref35
  doi: 10.3929/ethz-a-004284029
– ident: ref17
  doi: 10.1080/0305215X.2018.1444163
– ident: ref24
  doi: 10.1016/j.eswa.2019.113166
– ident: ref31
  doi: 10.1007/s00521-015-2073-y
– ident: ref26
  doi: 10.3390/a10040121
– ident: ref9
  doi: 10.1109/TSMCB.2012.2209115
– ident: ref1
  doi: 10.1002/nav.3800010110
– ident: ref3
  doi: 10.1287/moor.1.2.117
– ident: ref19
  doi: 10.1016/j.cor.2019.104839
– ident: ref13
  doi: 10.1007/s10951-020-00637-8
– ident: ref15
  doi: 10.1080/01605682.2019.1671149
– ident: ref18
  doi: 10.1016/j.cie.2017.06.025
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Snippet The Mixed No-Idle Flow-shop Scheduling Problem (MNIFSP) is an extension of flow-shop scheduling, which has practical significance and application prospects in...
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SubjectTerms mixed no-idle flow-shop scheduling problem (mnlfsp)
multidirection update
multiobjective optimization
particle swarm optimization (pso)
Title Multidirection Update-Based Multiobjective Particle Swarm Optimization for Mixed No-Idle Flow-Shop Scheduling Problem
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