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首页> 外文期刊>4OR: A Quarterly Journal of Operations Research >Min–max and min–max (relative) regret approaches to representatives selection problem
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Min–max and min–max (relative) regret approaches to representatives selection problem

机译:最小-最大和最小-最大(相对)后悔代表选择问题的方法

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摘要

The following optimization problem is studied. There are several sets of integer positive numbers whose values are uncertain. The problem is to select one representative of each set such that the sum of the selected numbers is minimum. The uncertainty is modeled by discrete and interval scenarios, and the min–max and min–max (relative) regret approaches are used for making a selection decision. The arising min–max, min–max regret and min–max relative regret optimization problems are shown to be polynomially solvable for interval scenarios. For discrete scenarios, they are proved to be NP-hard in the strong sense if the number of scenarios is part of the input. If it is part of the problem type, then they are NP-hard in the ordinary sense, pseudo-polynomially solvable by a dynamic programming algorithm and possess an FPTAS. This study is motivated by the problem of selecting tools of minimum total cost in the design of a production line.
机译:研究了以下优化问题。有几组整数正数,其值不确定。问题是要为每个集合选择一个代表,以使所选数字的总和最小。不确定性是通过离散和间隔场景建模的,并且使用最小-最大和最小-最大(相对)后悔方法来做出选择决策。出现的最小-最大,最小-最大后悔和最小-最大相对后悔优化问题对于区间场景可以多项式求解。对于离散场景,如果场景数量是输入的一部分,则从严格意义上讲,它们被证明是NP难的。如果它是问题类型的一部分,那么它们在一般意义上是NP难的,可以通过动态编程算法伪拟多项式地解决,并且具有FPTAS。这项研究的动机是在设计生产线时选择总成本最低的工具。

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