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A hybrid discrete water wave optimization algorithm for the no-idle flowshop scheduling problem with total tardiness criterion

机译:总时滞标准的无怠工流调度问题的混合离散水波优化算法

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The no-idle flowshop has attracted enormous attention owing to its widespread application in the manufacturing industry domain. In this paper, a hybrid discrete water wave optimization algorithm, named HWWO, is presented to solve the NIFSP with total tardiness. In order to improve the quality of a population, an initialize method based on a new priority rule combined with the modified NEH method is proposed to generate a population. In the propagation phase, a self-adaption selection neighborhood search structure is introduced to amplify the search range of waves and balance the exploration and exploitation ability of the HWWO. Afterwards, a variable neighborhood search is adopted to strengthen the local search and maintain the diversity of the population in the breaking phase. In the refraction operation, a perturbation sequence is generated and combined with the local optimal solution found by the breaking operation, in order to generate a new solution, and prevent the algorithm from becoming trapped in the local optimum. Furthermore, the control parameters and time complexity are analyzed. The experimental results and comparisons with the other state-of-the-art algorithms evaluated on Taillard's and Ruiz's benchmark sets reveal that the effectiveness and efficiency of the HWWO outperformed the compared algorithms for solving the NIFSP. (C) 2019 Elsevier Ltd. All rights reserved.
机译:无空流水车间因其在制造业领域的广泛应用而备受关注。提出了一种混合离散水波优化算法,称为HWWO,以解决总时延问题。为了提高种群的质量,提出了一种基于新优先级规则的初始化方法,并结合改进的NEH方法生成种群。在传播阶段,引入了自适应选择邻域搜索结构,以放大波的搜索范围,平衡HWWO的勘探开发能力。之后,采用可变邻域搜索来加强局部搜索,并在突破阶段保持种群的多样性。在折射运算中,将生成一个扰动序列,并将其与通过中断运算找到的局部最优解组合,以生成新的解,并防止算法陷入局部最优中。此外,分析了控制参数和时间复杂度。实验结果以及与其他基于Taillard和Ruiz基准集评估的最新算法的比较表明,HWWO的有效性和效率优于解决NIFSP的比较算法。 (C)2019 Elsevier Ltd.保留所有权利。

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