An intelligent hybrid meta-heuristic for solving a case of no-wait two-stage flexible flow shop scheduling problem with unrelated parallel machines
An intelligent hybrid meta-heuristic for solving a case of no-wait two-stage flexible flow shop scheduling problem with unrelated parallel machines
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DOI：
10.1007/s00170-013-5375-1
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发表时间：
2014-01
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影响因子：
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通讯作者：
M. Rabiee;R. S. Rad;M. Mazinani;R. Shafaei
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文献类型：
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作者：
M. Rabiee;R. S. Rad;M. Mazinani;R. Shafaei
研究了无等待两阶段柔性流水车间调度问题（NWTSFFSSP），该问题考虑了并行机不相关、装配时间顺序相关、返工可能性和不同的准备时间等因素。在这项研究中使用的性能指标是最大完工时间（makespan）最小化。针对该问题的复杂性，提出了一种基于帝国主义竞争算法（伊卡），结合模拟退火（SA）、变邻域搜索（VNS）和遗传算法（GA）的智能混合算法（HA）。杂交进行，以克服这三种算法中的每一个现有的一些缺点，也为提高伊卡的能力。为了获得可靠的结果，田口方法被用来定义我们所提出的算法的鲁棒参数的值。仿真模型的开发，以研究我们提出的算法对伊卡，SA，VNS，GA和蚁群优化（ACO）的性能。研究结果表明，HA研究的相对优势。此外，潜在的进一步研究领域的突出。
This paper addresses the problem of no-wait two-stage flexible flow shop scheduling problem (NWTSFFSSP) considering unrelated parallel machines, sequence-dependent setup times, probable reworks and different ready times to actualize the problem. The performance measure used in this study is minimizing maximum completion time (makespan). Because of the complexity of addressed problem, we propose a novel intelligent hybrid algorithm [called hybrid algorithm (HA)] based on imperialist competitive algorithm (ICA) which are combined with simulated annealing (SA), variable neighborhood search (VNS) and genetic algorithm (GA) for solving the mentioned problem. The hybridization is carried out to overcome some existing drawbacks of each of these three algorithms and also for increasing the capability of ICA. To achieve reliable results, Taguchi approach is used to define robust parameters' values for our proposed algorithm. A simulation model is developed to study the performance of our proposed algorithm against ICA, SA, VNS, GA and ant colony optimization (ACO). The results of the study reveal the relative superiority of HA studied. In addition, potential areas for further researches are highlighted.