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Distributed Flow Shop Scheduling with Sequence-Dependent Setup Times Using an Improved Iterated Greedy Algorithm 被引量:11
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作者 Xue Han Yuyan Han +5 位作者 qingda chen Junqing Li Hongyan Sang Yiping Liu Quanke Pan Yusuke Nojima 《Complex System Modeling and Simulation》 2021年第3期198-217,共20页
To meet the multi-cooperation production demand of enterprises,the distributed permutation flow shop scheduling problem(DPFSP)has become the frontier research in the field of manufacturing systems.In this paper,we inv... To meet the multi-cooperation production demand of enterprises,the distributed permutation flow shop scheduling problem(DPFSP)has become the frontier research in the field of manufacturing systems.In this paper,we investigate the DPFSP by minimizing a makespan criterion under the constraint of sequence-dependent setup times.To solve DPFSPs,significant developments of some metaheuristic algorithms are necessary.In this context,a simple and effective improved iterated greedy(NIG)algorithm is proposed to minimize makespan in DPFSPs.According to the features of DPFSPs,a two-stage local search based on single job swapping and job block swapping within the key factory is designed in the proposed algorithm.We compare the proposed algorithm with state-of-the-art algorithms,including the iterative greedy algorithm(2019),iterative greedy proposed by Ruiz and Pan(2019),discrete differential evolution algorithm(2018),discrete artificial bee colony(2018),and artificial chemical reaction optimization(2017).Simulation results show that NIG outperforms the compared algorithms. 展开更多
关键词 distributed permutation flow shop iterated greedy local search swapping strategy
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