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Digital twin oriented multi-objective flexible job shop scheduling model and its hybrid particle swarm optimization
Chen, Zhaoming1,2; Zou, Jinsong3; Wang, Wei4
2022-09-09
摘要To solve the problems of low efficiency and insufficient dynamic response of job shop scheduling in the discrete manufacturing process, a multi-objective flexible job shop scheduling model for digital twin and its solution method are proposed. Firstly, a digital twin scheduling model with physical entity, virtual model and production plan is constructed, and four factors are taken as optimization goals. Then, a hybrid particle swarm optimization method is designed to increase the refined optimization ability, and the obtained Pareto optimal solution set is analyzed by grey relational analysis to obtain a satisfactory solution which coincides with the actual production. Finally, a three-dimensional model which is completely mapped with the real job shop scheduling is built by Plant Simulation software. The scheduling process is simulated and optimized by combining with the production data of an enterprise, which verifies the feasibility and applicability of this method, and will effectively guide the production practice.
关键词Digital twin flexible job shop scheduling problem multi-objective optimization hybrid particle swarm algorithm simulated annealing
DOI10.1177/09544054221121921
发表期刊PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE
ISSN0954-4054
页码14
通讯作者Chen, Zhaoming(zhaomingc_sc@163.com)
收录类别SCI
WOS记录号WOS:000852321600001
语种英语