PTAS for Ordered Instances of Resource Allocation Problems with Restrictions on Inclusions

K. Khodamoradi, Ramesh Krishnamurti, A. Rafiey, G. Stamoulis
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引用次数: 10

Abstract

We consider the problem of fair allocation of indivisible goods where we are given a set I of m indivisible resources (items) and a set P of n customers (players) competing for the resources. Each resource j in I has a same value vj > 0 for a subset of customers interested in j and it has no value for other customers. The goal is to find a feasible allocation of the resources to the interested customers such that in the Max-Min scenario (also known as Santa Claus problem) the minimum utility (sum of the resources) received by each of the customers is as high as possible and in the Min-Max case (also known as R||C_max problem), the maximum utility is as low as possible. In this paper we are interested in instances of the problem that admit a PTAS. These instances are not only of theoretical interest but also have practical applications. For the Max-Min allocation problem, we start with instances of the problem that can be viewed as a convex bipartite graph; there exists an ordering of the resources such that each customer is interested (has positive evaluation) in a set of consecutive resources and we demonstrate a PTAS. For the Min-Max allocation problem, we obtain a PTAS for instances in which there is an ordering of the customers (machines) and each resource (job) is adjacent to a consecutive set of customers (machines). Next we show that our method for the Max-Min scenario, can be extended to a broader class of bipartite graphs where the resources can be viewed as a tree and each customer is interested in a sub-tree of a bounded number of leaves of this tree (e.g. a sub-path).
包含限制的资源分配问题的有序实例的PTAS
我们考虑不可分割商品的公平分配问题,其中给定集合I(包含m个不可分割资源(物品))和集合P(包含n个争夺资源的客户(玩家))。对于对j感兴趣的客户子集,I中的每个资源j具有相同的值vj > 0,并且对于其他客户没有值。目标是为感兴趣的客户找到一个可行的资源分配,这样在Max-Min场景(也称为圣诞老人问题)中,每个客户收到的最小效用(资源的总数)尽可能高,而在Min-Max情况(也称为R||C_max问题)中,最大效用尽可能低。在本文中,我们感兴趣的问题的实例,承认一个PTAS。这些实例不仅具有理论意义,而且具有实际应用价值。对于Max-Min分配问题,我们从可以看作凸二部图的问题实例开始;存在一个资源排序,使得每个客户对一组连续的资源感兴趣(有积极的评价),我们演示了一个PTAS。对于最小-最大分配问题,我们获得了客户(机器)排序的实例的PTAS,其中每个资源(作业)与一组连续的客户(机器)相邻。接下来,我们展示了我们用于最大最小场景的方法,可以扩展到更广泛的二部图类,其中资源可以被视为一棵树,每个客户对这棵树的有限数量的叶子(例如子路径)的子树感兴趣。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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