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Complexity of the Min-Max (Regret) Versions of Cut Problems

机译:裁切问题的最小-最大(遗憾)版本的复杂性

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This paper investigates the complexity of the min-max and min-max regret versions of the s — t min cut and min cut problems. Even if the underlying problems are closely related and both polynomial, we show that the complexity of their min-max and min-max regret versions, for a constant number of scenarios, are quite contrasted since they are respectively strongly NP-hard and polynomial. Thus, we exhibit the first polynomial problem, s — t min cut, whose min-max (regret) versions are strongly NP-hard. Also, min cut is one of the few polynomial problems whose min-max (regret) versions remain polynomial. However, these versions become strongly NP-hard for a non constant number of scenarios. In the interval data case, min-max versions are trivially polynomial. Moreover, for min-max regret versions, we obtain the same contrasted result as for a constant number of scenarios: min-max regret s — t cut is strongly NP-hard whereas min-max regret cut is polynomial.
机译:本文研究了s-t min cut和min cut问题的min-max和min-max后悔版本的复杂性。即使基本问题和两个多项式都密切相关,我们也表明,在一定数量的情况下,它们的min-max和min-max后悔版本的复杂性却形成了鲜明的对比,因为它们分别是强NP-hard和多项式。因此,我们展示了第一个多项式问题s-t min cut,其min-max(后悔)版本强烈为NP-hard。同样,最小割是少数多项式问题之一,其最小-最大值(后悔)版本仍然是多项式。但是,对于非恒定数量的方案,这些版本对NP来说非常困难。在间隔数据的情况下,最小值-最大值版本是平凡的多项式。此外,对于最小-最大后悔版本,我们获得与恒定数量的场景相同的对比结果:最小-最大后悔s-t cut是强烈的NP-hard,而最小-最大后悔切割是多项式。

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