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Journal ArticleDOI

Approximation algorithms for metric facility location and k-Median problems using the primal-dual schema and Lagrangian relaxation

Kamal Jain, +1 more
- 01 Mar 2001 - 
- Vol. 48, Iss: 2, pp 274-296
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TLDR
A new extension of the primal-dual schema and the use of Lagrangian relaxation to derive approximation algorithms for the metric uncapacitated facility location problem and the metric k-median problem achieving guarantees of 3 and 6 respectively.
Abstract
We present approximation algorithms for the metric uncapacitated facility location problem and the metric k-median problem achieving guarantees of 3 and 6 respectively. The distinguishing feature of our algorithms is their low running time: O(m logm) and O(m logm(L + log (n))) respectively, where n and m are the total number of vertices and edges in the underlying complete bipartite graph on cities and facilities. The main algorithmic ideas are a new extension of the primal-dual schema and the use of Lagrangian relaxation to derive approximation algorithms.

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Citations
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References
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Book

Integer and Combinatorial Optimization

TL;DR: This chapter discusses the Scope of Integer and Combinatorial Optimization, as well as applications of Special-Purpose Algorithms and Matching.
Journal ArticleDOI

Maximum matching and a polyhedron with 0,1-vertices

TL;DR: The emphasis in this paper is on relating the matching problem to the theory of continuous linear programming, and the algorithm described does not involve any "blind-alley programming" -which, essentially, amounts to testing a great many combinations.
Book ChapterDOI

A Heuristic Program for Locating Warehouses

TL;DR: The heuristic approach outlined in this paper appears to offer significant advantages in the solution of this class of problems in that it provides considerable flexibility in the specification (modeling) of the problem to be solved and is economical of computer time.
Journal ArticleDOI

A General Approximation Technique for Constrained Forest Problems

TL;DR: The first approximation algorithms for many NP-complete problems, including the non-fixed point-to-point connection problem, the exact path partitioning problem and complex location-design problems are derived.
Proceedings ArticleDOI

Probabilistic approximation of metric spaces and its algorithmic applications

Yair Bartal
TL;DR: It is proved that any metric space can be probabilistically-approximated by hierarchically well-separated trees (HST) with a polylogarithmic distortion.
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