文献类型：期刊文献

英文题名：Distributed Flexible Job-Shop Scheduling Problem Based on Hybrid Chemical Reaction Optimization Algorithm

作者：Li, Jialei[1];Gu, Xingsheng[1];Zhang, Yaya[1];Zhou, Xin[1]

机构：[1]East China Univ Sci & Technol, Lab Smart Mfg Energy Chem Proc, Minist Educ, Shanghai 200237, Peoples R China

年份：2022

卷号：2

期号：2

起止页码：156

外文期刊名：COMPLEX SYSTEM MODELING AND SIMULATION

收录：EI(收录号：20233214494692);WOS:【ESCI(收录号:WOS:001543510000004)】；

基金：Acknowledgment This work was supported by the National Natural Science Foundation of China (Nos. 61973120, 62076095, 61673175, and 61573144) .

语种：英文

外文关键词：scheduling problem; distributed flexible job-shop; chemical reaction optimization algorithm; heterogeneous factory; simulated annealing algorithm

摘要：Economic globalization has transformed many manufacturing enterprises from a single-plant production mode to a multi-plant cooperative production mode. The distributed flexible job-shop scheduling problem (DFJSP) has become a research hot topic in the field of scheduling because its production is closer to reality. The research of DFJSP is of great significance to the organization and management of actual production process. To solve the heterogeneous DFJSP with minimal completion time, a hybrid chemical reaction optimization (HCRO) algorithm is proposed in this paper. Firstly, a novel encoding-decoding method for flexible manufacturing unit (FMU) is designed. Secondly, half of initial populations are generated by scheduling rule. Combined with the new solution acceptance method of simulated annealing (SA) algorithm, an improved method of critical-FMU is designed to improve the global and local search ability of the algorithm. Finally, the elitist selection strategy and the orthogonal experimental method are introduced to the algorithm to improve the convergence speed and optimize the algorithm parameters. In the experimental part, the effectiveness of the simulated annealing algorithm and the critical-FMU refinement methods is firstly verified. Secondly, in the comparison with other existing algorithms, the proposed optimal scheduling algorithm is not only effective in homogeneous FMUs examples, but also superior to existing algorithms in heterogeneous FMUs arithmetic cases.