用离散人工蜂群算法求解具有总流时间准则的置换流水车间调度问题

M. Tasgetiren, Q. Pan, P. N. Suganthan, A. Chen
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引用次数: 29

摘要

最近,Jarboui等人[1](计算机与运筹学36(2009)2638-2646)和Tseng和Lin[2](欧洲运筹学杂志198(2009)84-92)分别提出了一种新的估计分布算法(EDA)和混合遗传局部搜索(hGLS)算法,用于具有总流程时间(TFT)标准的置换流水车间调度(PFSP)。这两种算法都产生了出色的结果,从而改进了迄今为止文献中报道的所有最知名的解决方案。然而,在本文中,我们提出了一种离散人工蜂群(DABC)算法,该算法将迭代贪婪(IG)和迭代局部搜索(ILS)算法混合在基于交换和插入邻域结构的可变邻域搜索(VNS)过程中。我们还提出了采用IG和VNS结构的先前离散差分进化(hDDE)算法的混合版本。DABC和hDDE的性能在解决方案质量和CPU时间方面与EDA和hGLS算法具有很强的竞争力。最终,EDA和hGLS算法最近提供的60个最著名的解决方案中有43个通过DABC和hDDE算法进一步改进了短期搜索。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A discrete artificial bee colony algorithm for the permutation flow shop scheduling problem with total flowtime criterion
Very recently, Jarboui et al. [1] (Computers & Operations Research 36 (2009) 2638–2646) and Tseng and Lin [2] (European Journal of Operational Research 198 (2009) 84–92) presented a novel estimation distribution algorithm (EDA) and a hybrid genetic local search (hGLS) algorithm for the permutation flowshop scheduling (PFSP) with the total flowtime (TFT) criterion, respectively. Both algorithms generated excellent results, thus improving all the best known solutions reported in the literature so far. However, in this paper, we present a discrete artificial bee colony (DABC) algorithm hybridized with an iterated greedy (IG) and iterated local search (ILS) algorithms embedded in a variable neighborhood search (VNS) procedure based on swap and insertion neighborhood structures. We also present a hybrid version of our previous discrete differential evolution (hDDE) algorithm employing the IG and VNS structure too. The performance of the DABC and hDDE is highly competitive to the EDA and hGLS algorithms in terms of both solution quality and CPU times. Ultimately, 43 out of 60 best known solutions provided very recently by the EDA and hGLS algorithms are further improved by the DABC and hDDE algorithms with short-term search.
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