To solve the distributed flexible job shop scheduling problem considering the transportation time of workpieces between machines(DFJSPTW),this study proposed an improved algorithm based on late ac-ceptance hill climbing algorithm(LAHC)and established a mathematical model with the maximum com-pletion time as the optimization objective.Firstly,to address the coupled sub-problems of DFJSPTW,inclu-ding factory allocation,machine selection,and operation sequencing,a three-tier chromosome encoding method based on operations,machines,and factories is employed.Additionally,a scheduling rule consider-ing load balancing is proposed for AGV allocation.To improve the quality of generated solutions,load bal-ancing is taken into account separately for factory and machine sequences during the initialization of chro-mosomes.During the local searching,the algorithm is designed with four types of neighborhood search op-erators and proposed a variable neighborhood search strategy that were compatible with DFJSPTW.Addi-tionally,when switching between neighborhood search operators,a single-molecule reaction search mecha-nism inspired by the chemical reaction algorithm is introduced to enhance the algorithm's comprehensive search capability.The effectiveness of the variable neighborhood search strategy and the introduction of the single-molecule reaction search mechanism were validated through numerical experiments.Furthermore,comparative experiments with the improved algorithm against GA_OP and GA_JS algorithms were conduc-ted to further confirm the superiority of the proposed algorithm in solving DFJSPTW.
flexible job shop schedulingdistributed schedulingthe transportation time of workpiecessin-gle-objective optimization
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