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发布时间：2019-03-11

论文类型：会议论文

发表时间：2013-06-27

收录刊物：Scopus、CPCI-S、EI

页面范围：427-432

关键字：flexible job shop scheduling problem; automatic guided vehicle; artificial bee colony; micro genetic algorithm

摘要：We deal with multi-objective Flexible Job Shop Scheduling Problem (FJSSP) with transportation resources constraints herein, where the cost time of loaded and empty Automatic Guided Vehicle (AGV) cannot be neglected. This problem is a NP-hard problem, whose optimization objectives are to minimize the makespan and total workload of machines. We proposed a multi-objective micro artificial bee colony algorithm (MMABC) to tackle this problem. In MMABC, each solution corresponds to a food source, which is encoded to reflect the assignment of AGV tasks, machine operations, and operation sequence; the smaller bee population is divided in two parts: a replaceable bee part and non-replaceable bee part. We also employed the crossover operator to the employed bee for exchanging the good scheduling. Experimental results on larger examples and comparisons with multi-objective micro genetic algorithm showed the effectiveness of the proposed algorithm.