Improving NSGA-III Algorithm for Solving High-dimensional Many-objective Green Flexible Job Shop Scheduling Problem

Authors

Yigang Xu, College of Mechanical Engineering, Hubei Institute of Automotive Technology, Shiyan 442000, China
Yong Chen, College of Mechanical Engineering, Hubei Institute of Automotive Technology, Shiyan 442000, China; Shiyan Industrial Technology Research Institute of China Engineering Science and Technology, Shiyan 442000, China
Chen Wang, College of Mechanical Engineering, Hubei Institute of Automotive Technology, Shiyan 442000, China; Shiyan Industrial Technology Research Institute of China Engineering Science and Technology, Shiyan 442000, China; Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, Shanghai University, Shanghai 200072, China
Yunxian Peng, Dongfeng Special Purpose Vehicle Co., Ltd, Shiyan 442000, China

Abstract

Abstract: Aiming at the poor initial solution quality and low local search efficiency of NSGA-III in solving the many-objective flexible job shop scheduling model, an improved NSGA-III (NSGA-III-TV) is proposed. Based on MSOS encoding, the different mixed initialization strategies are adopted for OS and MS chromosomes to improve the quality of initial solutions. Based on the critical path, an improved N6 neighborhood structure is used for neighborhood search, which effectively reduce the completion time and reducing search randomness. Three effective mutation operators are employed to expand the search space and improve the convergence capability in the later stages. Test results show that NSGA-III-TV has good performance and practicality in solving the high-dimensional many-objective flexible job shop scheduling problems, which provides strong support for the intelligent green transformation and the upgrading of manufacturing workshops of enterprises

Recommended Citation

Xu, Yigang; Chen, Yong; Wang, Chen; and Peng, Yunxian (2024) "Improving NSGA-III Algorithm for Solving High-dimensional Many-objective Green Flexible Job Shop Scheduling Problem," Journal of System Simulation: Vol. 36: Iss. 10, Article 9.
DOI: 10.16182/j.issn1004731x.joss.23-0694
Available at: https://dc-china-simulation.researchcommons.org/journal/vol36/iss10/9

First Page

2314

Last Page

2329

CLC

TP18; TH165

Recommended Citation

Xu Yigang, Chen Yong, Wang Chen, et al. Improving NSGA-III Algorithm for Solving High-dimensional Many-objective Green Flexible Job Shop Scheduling Problem[J]. Journal of System Simulation, 2024, 36(10): 2314-2329.

Corresponding Author

Chen Yong

DOI

10.16182/j.issn1004731x.joss.23-0694