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首页> 外文期刊>Frontiers of mechanical engineering >Pareto lexicographic α-robust approach and its application in robust multi objective assembly line balancing problem
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Pareto lexicographic α-robust approach and its application in robust multi objective assembly line balancing problem

机译:Pareto词典编排α-鲁棒方法及其在鲁棒多目标装配线平衡问题中的应用

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摘要

Robustness in most of the literature is associated with min-max or min-max regret criteria. However, these criteria of robustness are conservative and therefore recently new criteria called, lexicographic α-robust method has been introduced in literature which defines the robust solution as a set of solutions whose quality or jth largest cost is not worse than the best possible jth largest cost in all scenarios. These criteria might be significant for robust optimization of single objective optimization problems. However, in real optimization problems, two or more than two conflicting objectives are desired to optimize concurrently and solution of multi objective optimization problems exists in the form of a set of solutions called Pareto solutions and from these solutions it might be difficult to decide which Pareto solution can satisfy min-max, min-max regret or lexicographic α-robust criteria by considering multiple objectives simultaneously. Therefore, lexicographic α-robust method which is a recently introduced method in literature is extended in the current research for Pareto solutions. The proposed method called Pareto lexicographic α-robust approach can define Pareto lexicographic α-robust solutions from different scenarios by considering multiple objectives simultaneously. A simple example and an application of the proposed method on a simple problem of multi objective optimization of simple assembly line balancing problem with task time uncertainty is presented to get their robust solutions. The presented method can be significant to implement on different multi objective robust optimization problems containing uncertainty.
机译:大多数文献中的鲁棒性与最小-最大或最小-最大后悔标准相关。但是,这些鲁棒性标准是保守的,因此最近在文献中引入了称为词典词典α-鲁棒方法的新标准,该标准将鲁棒性解决方案定义为一组解决方案,这些解决方案的质量或第j个最大成本不比最好的第j个最大成本差。在所有情况下的成本。这些标准对于单目标优化问题的鲁棒优化可能很重要。但是,在实际的优化问题中,需要两个或两个以上相互矛盾的目标来同时进行优化,而多目标优化问题的解决方案是以称为Pareto解决方案的一组解决方案的形式存在的,从这些解决方案中可能很难决定哪个Pareto通过同时考虑多个目标,解决方案可以满足最小-最大,最小-最大后悔或词典α-鲁棒标准。因此,在当前对帕累托解的研究中扩展了文献中最近引入的词典编排α-鲁棒法。所提出的称为Pareto词典编排α-鲁棒方法的方法可以通过同时考虑多个目标来定义来自不同场景的Pareto词典编排α-鲁棒解。给出了带有任务时间不确定性的简单装配线平衡问题的多目标优化的简单问题的简单实例和所提出方法的应用,以获得其鲁棒的解决方案。所提出的方法对于解决包含不确定性的不同多目标鲁棒优化问题具有重要意义。

著录项

  • 来源
    《Frontiers of mechanical engineering》 |2014年第3期|257-264|共8页
  • 作者单位

    HUST-SANY Joint Laboratory of Advanced Manufacturing Technology, Huazhong University of Science and Technology, Wuhan 430074, China,Department of Industrial Engineering, University of Engineering and Technology, Taxila, Pakistan;

    HUST-SANY Joint Laboratory of Advanced Manufacturing Technology, Huazhong University of Science and Technology, Wuhan 430074, China;

    HUST-SANY Joint Laboratory of Advanced Manufacturing Technology, Huazhong University of Science and Technology, Wuhan 430074, China;

    Department of Industrial Engineering, University of Engineering and Technology, Taxila, Pakistan;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Pareto; lexicographic α-robust; assembly line balancing;

    机译:帕累托字典式α-鲁棒;流水线平衡;

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