Hybrid Particle Swarm Optimization for Hybrid Flowshop Scheduling Problem with Maintenance Activities

A hybrid algorithm which combines particle swarm optimization (PSO) and iterated local search (ILS) is proposed for solving the hybrid flowshop scheduling (HFS) problem with preventive maintenance (PM) activities. In the proposed algorithm, different crossover operators and mutation operators are in...

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Main Authors: Jun-qing Li, Quan-ke Pan, Kun Mao
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2014/596850
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author Jun-qing Li
Quan-ke Pan
Kun Mao
author_facet Jun-qing Li
Quan-ke Pan
Kun Mao
author_sort Jun-qing Li
collection DOAJ
description A hybrid algorithm which combines particle swarm optimization (PSO) and iterated local search (ILS) is proposed for solving the hybrid flowshop scheduling (HFS) problem with preventive maintenance (PM) activities. In the proposed algorithm, different crossover operators and mutation operators are investigated. In addition, an efficient multiple insert mutation operator is developed for enhancing the searching ability of the algorithm. Furthermore, an ILS-based local search procedure is embedded in the algorithm to improve the exploitation ability of the proposed algorithm. The detailed experimental parameter for the canonical PSO is tuning. The proposed algorithm is tested on the variation of 77 Carlier and Néron’s benchmark problems. Detailed comparisons with the present efficient algorithms, including hGA, ILS, PSO, and IG, verify the efficiency and effectiveness of the proposed algorithm.
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issn 2356-6140
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language English
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publisher Wiley
record_format Article
series The Scientific World Journal
spelling doaj-art-6dfea928498c411aba19b00d39fec6752025-02-03T05:51:57ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/596850596850Hybrid Particle Swarm Optimization for Hybrid Flowshop Scheduling Problem with Maintenance ActivitiesJun-qing Li0Quan-ke Pan1Kun Mao2State Key Laboratory of Synthetic Automation for Process Industries, Northeastern University, Shenyang 110819, ChinaState Key Laboratory of Synthetic Automation for Process Industries, Northeastern University, Shenyang 110819, ChinaState Key Laboratory of Synthetic Automation for Process Industries, Northeastern University, Shenyang 110819, ChinaA hybrid algorithm which combines particle swarm optimization (PSO) and iterated local search (ILS) is proposed for solving the hybrid flowshop scheduling (HFS) problem with preventive maintenance (PM) activities. In the proposed algorithm, different crossover operators and mutation operators are investigated. In addition, an efficient multiple insert mutation operator is developed for enhancing the searching ability of the algorithm. Furthermore, an ILS-based local search procedure is embedded in the algorithm to improve the exploitation ability of the proposed algorithm. The detailed experimental parameter for the canonical PSO is tuning. The proposed algorithm is tested on the variation of 77 Carlier and Néron’s benchmark problems. Detailed comparisons with the present efficient algorithms, including hGA, ILS, PSO, and IG, verify the efficiency and effectiveness of the proposed algorithm.http://dx.doi.org/10.1155/2014/596850
spellingShingle Jun-qing Li
Quan-ke Pan
Kun Mao
Hybrid Particle Swarm Optimization for Hybrid Flowshop Scheduling Problem with Maintenance Activities
The Scientific World Journal
title Hybrid Particle Swarm Optimization for Hybrid Flowshop Scheduling Problem with Maintenance Activities
title_full Hybrid Particle Swarm Optimization for Hybrid Flowshop Scheduling Problem with Maintenance Activities
title_fullStr Hybrid Particle Swarm Optimization for Hybrid Flowshop Scheduling Problem with Maintenance Activities
title_full_unstemmed Hybrid Particle Swarm Optimization for Hybrid Flowshop Scheduling Problem with Maintenance Activities
title_short Hybrid Particle Swarm Optimization for Hybrid Flowshop Scheduling Problem with Maintenance Activities
title_sort hybrid particle swarm optimization for hybrid flowshop scheduling problem with maintenance activities
url http://dx.doi.org/10.1155/2014/596850
work_keys_str_mv AT junqingli hybridparticleswarmoptimizationforhybridflowshopschedulingproblemwithmaintenanceactivities
AT quankepan hybridparticleswarmoptimizationforhybridflowshopschedulingproblemwithmaintenanceactivities
AT kunmao hybridparticleswarmoptimizationforhybridflowshopschedulingproblemwithmaintenanceactivities