钢桥板单元分布式柔性作业车间成组调度OA

To address the issue of slow production speed of steel bridge plate units,which directly constrained the construction period of bridge engineering projects,a distributed flexible job-shop group scheduling problem with setup&transportation time(DFJGSPST)model for steel bridge plate unit processing was established to minimize the maximum completion time while considering the processing technology route and production characteristics.A memory-based genetic algorithm with tabu search(MGATS)based on a three-layer encoding strategy was proposed to solve the model.To verify the feasibility of the mathematical model and intelligent algorithm,a DFJGSPST model comprising four types of plate unit groups and fifteen machines was established using a real-world steel bridge plate unit production case.Relevant test instances were selected for experimental validation and comparative analysis with other intelligent algorithms.Experimental results showed that the proposed MGATS algorithm achieved a mean rela-tive percentage difference(RPD)of 2.74%,which was lower than that of the genetic algorithm(GA)at 3.99%,and hybrid genetic tabu search algorithm(GATS)at 3.13%.The success rate(SR)of the MGATS algorithm was 0.15,which was higher than that of the GATS algorithm and the GA algorithm,which verified the stability and ro-bustness of the MGATS algorithm in solving the DFJGSPST model.