An overview of representative problems in location research
Management Science
e-approximations with minimum packing constraint violation (extended abstract)
STOC '92 Proceedings of the twenty-fourth annual ACM symposium on Theory of computing
Approximation schemes for Euclidean k-medians and related problems
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
Greedy strikes back: improved facility location algorithms
Journal of Algorithms
Local search heuristic for k-median and facility location problems
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
A new greedy approach for facility location problems
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
SIAM Journal on Computing
A general approach for incremental approximation and hierarchical clustering
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Better bounds for incremental medians
WAOA'07 Proceedings of the 5th international conference on Approximation and online algorithms
Oblivious medians via online bidding
LATIN'06 Proceedings of the 7th Latin American conference on Theoretical Informatics
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The incremental median problem consists of finding an incremental sequence of facility sets F1 ⊆ F2 ⊆ ... ⊆ Fn, where each Fk contains at most k facilities. We say that this incremental medians sequence is c-competitive if the cost of each Fk is at most c times of the optimum cost of k-median problem. The smallest such c is called the competitive ratio. A particular case of the problem is considered in this paper: both the clients and facilities are located on the real line. [5] and [14] presented a polynomial-time algorithm for this one-dimensional case that computes an incremental sequence with competitive ratio 8. The best algorithm available has competitive ratio (1 + √2)2 ≈ 5.83[19]. In this paper we give an improved polynomial-time algorithm with competitive factor 4.