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Approximation of min-max and min-max regret versions of some combinatorial optimization problems

机译:一些组合优化问题的min-max和min-max后悔版本的逼近

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摘要

This paper investigates, for the first time in the literature, the approximation of min-max (regret) versions of classical problems like shortest path, minimum spanning tree, and knapsack. For a constant number of scenarios, we establish fully polynomial-time approximation schemes for the min-max versions of these problems, using relationships between multi-objective and min-max optimization. Using dynamic programming and classical trimming techniques, we construct a fully polynomial-time approximation scheme for min-max regret shortest path. We also establish a fully polynomial-time approximation scheme for min-max regret spanning tree and prove that min-max regret knapsack is not at all approximable. For a non-constat number of scenarios, in which case min max and min-max regret versions of polynomial-time solvable problems usually become strongly NP-hard, non-approximability results are provided for min-max (regret) versions of shortest path and spanning tree. (c) 2006 Elsevier B.V. All rights reserved.
机译:本文是文献中首次研究最小问题,最短生成树和背包等经典问题的最小-最大(后悔)版本的近似值。对于恒定数量的场景,我们使用多目标优化和最小-最大优化之间的关系为这些问题的最小-最大版本建立完全多项式时间近似方案。使用动态规划和经典修整技术,我们构造了最小-最大后悔最短路径的完全多项式时间近似方案。我们还建立了最小最大后悔生成树的完全多项式时间近似方案,并证明最小最大后悔背包根本不是近似的。对于非constat状态的情况,在这种情况下,多项式时间可解决问题的最小最大和最小最大后悔版本通常会变得很NP-难,为最短路径的最小-最大(后悔)版本提供了非近似结果和生成树。 (c)2006 Elsevier B.V.保留所有权利。

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