Improved GWO Algorithm for Flexible Job Shop Scheduling Problem
An improved neighborhood search gray wolf algorithm was designed for a flexible job shop scheduling problem with the objective of minimizing the maximum completion time.A two-layer encoding scheme was designed based on processes and machines suitable for the gray wolf algorithm,the population initialization strategy,the gray wolf mutation operation and the population update mechanism were improved.The global search neighborhood of the GWO algorithm was obtained by two-point crossover operation,inser-tion operation and PR operation,and then the forbidden search neighborhood was proposed to enhance the local exploitation capability of the GWO algorithm.Finally,the proposed algorithm was simulated and experimented on known examples and compared with other algo-rithms.The experimental results verify the superiority of the improved GWO algorithm.
gray wolf algorithmneighborhood searchforbidden searchflexible job shop scheduling
万方数据
维普
