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Improved Approximation Algorithm for k-level Uncapacitated Facility Location Problem (with Penalties)

机译:k级无能力设施选址问题的改进的近似算法(有惩罚)

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We study the k-level uncapacitated facility location problem (k-level UFL) in which clients need to be connected with paths crossing open facilities of k types (levels). In this paper we first propose an approximation algorithm that for any constant k, in polynomial time, delivers solutions of cost at most alpha (k) times OPT, where alpha (k) is an increasing function of k, with . Our algorithm rounds a fractional solution to an extended LP formulation of the problem. The rounding builds upon the technique of iteratively rounding fractional solutions on trees (Garg, Konjevod, and Ravi SODA'98) originally used for the group Steiner tree problem. We improve the approximation ratio for k-level UFL for all k a parts per thousand yen 3, in particular we obtain the ratio equal 2.02, 2.14, and 2.24 for k = 3,4, and 5. Second, we give a simple interpretation of the randomization process (Li ICALP'2011) for 1-level UFL in terms of solving an auxiliary (factor revealing) LP. Armed with this simple view point, we exercise the randomization on our algorithm for the k-level UFL. We further improve the approximation ratio for all k a parts per thousand yen 3, obtaining 1.97, 2.09, and 2.19 for k = 3,4, and 5. Third, we extend our algorithm to the k-level UFL with penalties (k-level UFLWP), in which the setting is the same as k-level UFL except that the planner has the option to pay a penalty instead of connecting chosen clients.
机译:我们研究了k级无能力设施定位问题(k级UFL),在该问题中,客户需要与跨越k个类型(级别)的开放式设施的路径连接。在本文中,我们首先提出一种近似算法,对于任意常数k,在多项式时间内,它的成本解最多为OPT的alpha(k)倍,其中alpha(k)是k的递增函数,其中。我们的算法将分数解四舍五入为问题的扩展LP公式。四舍五入的基础是对最初用于组Steiner树问题的树(Garg,Konjevod和Ravi SODA'98)迭代分数解的技术。对于所有千分之一千日元3,我们提高了k级UFL的近似比率,特别是对于k = 3,4和5,我们获得了等于2.02、2.14和2.24的比率。其次,我们对一级UFL的随机化过程(Li ICALP'2011),用于解决辅助(因子显示)LP。有了这个简单的观点,我们就对k级UFL的算法进行了随机化处理。我们进一步提高了所有ka部件/千日元3的逼近率,对于k = 3,4和5,获得了1.97、2.09和2.19。第三,我们将算法扩展到具有罚金的k级UFL(k级UFLWP),其设置与k级UFL相同,除了计划者可以选择支付罚金而不是连接选定的客户。

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