Flexible job-shop scheduling optimization algorithm based on Co-CEM
This paper proposes a cooperative coevolution-based CEM(Co-CEM)algorithm to solve the flexible job-shop scheduling problem(FJSP)in shipbuilding and improve the efficiency of the shipbuilding process.The co-e-volution strategy makes up for the weak local search capability of the cross-entropy method(CEM),thus achieving improved solution quality.In this paper,a genetic decoding algorithm based on active scheduling is proposed,in which the active scheduling operation ensures that the solutions obtained belong to active scheduling,and the genet-ic operation saves relevant scheduling information in the gene,effectively improving the search efficiency of the al-gorithm.The effectiveness of the proposed decoding algorithm and its improvement ability were verified by compa-ring the genetic decoding algorithm with the commonly used plug-in decoding algorithm via experiments.The com-parison with existing competitive algorithms proves the efficiency and superiority of Co-CEM,thereby yielding a cor-responding high-quality Gantt chart.
国家科技期刊平台
NSTL
万方数据
维普
