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

Authors

Jiang Li¹, Lihong Guo^{1, *}, Yan Li¹, Chang Liu¹, Lijuan Wang^2, , Hui Hu³

¹Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, 130033, China

²School of Computer, Jiangsu University of Science and Technology, Zhenjiang, 212003, China

³Department of Information Science and Technology, Huizhou University, Guangdong, 516007, China

^*Corresponding author. Email: guolh@ciomp.ac.cn

DOI

10.2991/ijcis.d.210112.002How to use a DOI?

Keywords

Whale optimization algorithm; Chaotic maps; Flow shop scheduling; Makespan; Local search; Cross selection

Abstract

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.

Copyright

© 2021 The Authors. Published by Atlantis Press B.V.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Jiang Li
AU  - Lihong Guo
AU  - Yan Li
AU  - Chang Liu
AU  - Lijuan Wang
AU  - Hui Hu
PY  - 2021
DA  - 2021/01/19
TI  - Enhancing Whale Optimization Algorithm with Chaotic Theory for Permutation Flow Shop Scheduling Problem
JO  - International Journal of Computational Intelligence Systems
SP  - 651
EP  - 675
VL  - 14
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.210112.002
DO  - 10.2991/ijcis.d.210112.002
ID  - Li2021
ER  -