Enhancing Whale Optimization Algorithm with Chaotic Theory for Permutation Flow Shop Scheduling Problem

The permutation flow shop scheduling problem (PFSSP) is a typical production scheduling problem and it has been proved to be a nondeterministic polynomial (NP-hard) problem when its scale is larger than 3. The whale optimization algorithm (WOA) is a new swarm intelligence algorithm which performs we...

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Main Authors: Jiang Li, Lihong Guo, Yan Li, Chang Liu, Lijuan Wang, Hui Hu
Format: Article
Language:English
Published: Springer 2021-01-01
Series:International Journal of Computational Intelligence Systems
Subjects:
Online Access:https://www.atlantis-press.com/article/125951267/view
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author Jiang Li
Lihong Guo
Yan Li
Chang Liu
Lijuan Wang
Hui Hu
author_facet Jiang Li
Lihong Guo
Yan Li
Chang Liu
Lijuan Wang
Hui Hu
author_sort Jiang Li
collection DOAJ
description The permutation flow shop scheduling problem (PFSSP) is a typical production scheduling problem and it has been proved to be a nondeterministic polynomial (NP-hard) problem when its scale is larger than 3. The whale optimization algorithm (WOA) is a new swarm intelligence algorithm which performs well for PFSSP. But the stability is still low, and the optimization results are not too good. On this basis, we optimize the parameters of WOA through chaos theory, and put forward a chaotic whale algorithm (CWA). Firstly, in this paper, the proposed CWA is combined with Nawaz–Ensco–Ham (NEH) and largest-rank-value (LRV) rule to initialize the population. Next, chaos theory is applied to WOA algorithm to improve its convergence speed and stability. On this basis, we also use cross operator and reversal-insertion operator to enhance the search ability of the algorithm. Finally, the improved local search algorithm is used to optimize the job sequence to find the minimum makespan. In several experiments, different benchmarks are used to investigate the performance of CWA. The experimental results show that CWA has better performance than other scheduling algorithms.
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spelling doaj.art-6580020879a74dab8c2eee36597d9e882022-12-22T02:11:06ZengSpringerInternational Journal of Computational Intelligence Systems1875-68832021-01-0114110.2991/ijcis.d.210112.002Enhancing Whale Optimization Algorithm with Chaotic Theory for Permutation Flow Shop Scheduling ProblemJiang LiLihong GuoYan LiChang LiuLijuan WangHui HuThe permutation flow shop scheduling problem (PFSSP) is a typical production scheduling problem and it has been proved to be a nondeterministic polynomial (NP-hard) problem when its scale is larger than 3. The whale optimization algorithm (WOA) is a new swarm intelligence algorithm which performs well for PFSSP. But the stability is still low, and the optimization results are not too good. On this basis, we optimize the parameters of WOA through chaos theory, and put forward a chaotic whale algorithm (CWA). Firstly, in this paper, the proposed CWA is combined with Nawaz–Ensco–Ham (NEH) and largest-rank-value (LRV) rule to initialize the population. Next, chaos theory is applied to WOA algorithm to improve its convergence speed and stability. On this basis, we also use cross operator and reversal-insertion operator to enhance the search ability of the algorithm. Finally, the improved local search algorithm is used to optimize the job sequence to find the minimum makespan. In several experiments, different benchmarks are used to investigate the performance of CWA. The experimental results show that CWA has better performance than other scheduling algorithms.https://www.atlantis-press.com/article/125951267/viewWhale optimization algorithmChaotic mapsFlow shop schedulingMakespanLocal searchCross selection
spellingShingle Jiang Li
Lihong Guo
Yan Li
Chang Liu
Lijuan Wang
Hui Hu
Enhancing Whale Optimization Algorithm with Chaotic Theory for Permutation Flow Shop Scheduling Problem
International Journal of Computational Intelligence Systems
Whale optimization algorithm
Chaotic maps
Flow shop scheduling
Makespan
Local search
Cross selection
title Enhancing Whale Optimization Algorithm with Chaotic Theory for Permutation Flow Shop Scheduling Problem
title_full Enhancing Whale Optimization Algorithm with Chaotic Theory for Permutation Flow Shop Scheduling Problem
title_fullStr Enhancing Whale Optimization Algorithm with Chaotic Theory for Permutation Flow Shop Scheduling Problem
title_full_unstemmed Enhancing Whale Optimization Algorithm with Chaotic Theory for Permutation Flow Shop Scheduling Problem
title_short Enhancing Whale Optimization Algorithm with Chaotic Theory for Permutation Flow Shop Scheduling Problem
title_sort enhancing whale optimization algorithm with chaotic theory for permutation flow shop scheduling problem
topic Whale optimization algorithm
Chaotic maps
Flow shop scheduling
Makespan
Local search
Cross selection
url https://www.atlantis-press.com/article/125951267/view
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AT lihongguo enhancingwhaleoptimizationalgorithmwithchaotictheoryforpermutationflowshopschedulingproblem
AT yanli enhancingwhaleoptimizationalgorithmwithchaotictheoryforpermutationflowshopschedulingproblem
AT changliu enhancingwhaleoptimizationalgorithmwithchaotictheoryforpermutationflowshopschedulingproblem
AT lijuanwang enhancingwhaleoptimizationalgorithmwithchaotictheoryforpermutationflowshopschedulingproblem
AT huihu enhancingwhaleoptimizationalgorithmwithchaotictheoryforpermutationflowshopschedulingproblem