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A Hybrid Imperialist Competitive Algorithm for the Flexible Job Shop Problem

机译:一种柔性作业店问题的混合帝国主义竞争算法

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Flexible job shop scheduling problem (FJSP) is one of the hardest combinatorial optimization problems known to be NP-hard. This paper proposes a novel hybrid imperialist competitive algorithm with simulated annealing (HICASA) for solving the FJSP. HICASA explores the search space by using imperial competitive algorithm (ICA) and use a simulated annealing (SA) algorithm for exploitation in the search space. In order to obtain reliable results from HICASA algorithm, a robust parameter design is applied. HICASA is compared with the widely-used genetic algorithm (GA) and the relatively new imperialist competitive algorithm (ICA). Experimental results suggest that HICASA algorithm is superior to GA and ICA on the FJSP.
机译:灵活的作业商店调度问题(FJSP)是已知为NP-HARD的最困难的组合优化问题之一。本文提出了一种新型混合帝国主义竞争算法,具有模拟退火(HiCasa)来解决FJSP。 HICasa使用帝国竞争算法(ICA)探索搜索空间,并使用模拟退火(SA)算法进行搜索空间中的开发。为了获得HiCasa算法的可靠结果,应用了一种强大的参数设计。将HICasa与广泛使用的遗传算法(GA)和相对较新的帝国主义竞争算法(ICA)进行比较。实验结果表明,HiCasa算法在FJSP上优于GA和ICA。

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