Affiliations: [a]
Information Construction and Management Center, Nanyang Institute of Technology, Nanyang, Henan, China
| [b]
School of Digital Media and Art Design, Nanyang Institute of Technology, Nanyang, Henan, China
Correspondence:
[*]
Corresponding author. Kaifeng Geng, Information Construction and Management Center, Nanyang Institute of Technology, Henan, China. E-mail: [email protected].
Abstract: Although re-entrant hybrid flow shop scheduling is widely used in industry, its processing and delivery times are typically determined using precise values that frequently ignore the influence of machine failure, human factors, the surrounding environment, and other uncertain factors, resulting in a significant gap between theoretical research and practical application. For fuzzy re-entrant hybrid flow shop scheduling problem (FRHFSP), an integrated scheduling model is established to minimize the maximum completion time and maximize the average agreement index. According to the characteristics of the problem, a hybrid NSGA-II (HNSGA-II) algorithm is designed. Firstly, a two-layer encoding strategy based on operation and machine is designed; Then, a hybrid population initialization method is designed to improve the quality of the initial population; At the same time, crossover and mutation operators and five neighborhood search operators are designed to enhance the global and local search ability of the algorithm; Finally, a large number of simulation experiments verify the effectiveness and superiority of the algorithm.
Keywords: Re-entrant hybrid flow shop, multi objective optimization, fuzzy scheduling, average agreement index
