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The Fair OWA One-to-One Assignment Problem: NP-Hardness and Polynomial Time Special Cases

机译:公平的OWA一对一分配问题:NP硬度和多项式时间特例

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We consider a one-to-one assignment problem consisting of matching n objects with n agents. Any matching leads to a utility vector whose n components measure the satisfaction of the various agents. We want to find an assignment maximizing a global utility defined as an ordered weighted average (OWA) of the n individual utilities. OWA weights are assumed to be non-increasing with ranks of satisfaction so as to include an idea of fairness in the definition of social utility. We first prove that the problem is NP-hard; then we propose a polynomial algorithm under some restrictions on the set of admissible weight vectors, proving that the problem belongs to XP.
机译:我们考虑由n个对象与n个代理匹配组成的一对一分配问题。任何匹配都会导致效用向量,其效用向量的n个分量可衡量各种代理的满意度。我们想要找到一个最大化全局效用的赋值,该全局效用定义为n个单个效用的有序加权平均值(OWA)。 OWA权重随着满意度的增加而不会增加,以便在社会效用的定义中包含公平的概念。我们首先证明问题是NP难的;然后我们在允许的权重向量集合的一些限制下提出了多项式算法,证明了问题属于XP。

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