Approximation Algorithms for Minimum-Load k -Facility Location
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چکیده
منابع مشابه
Approximation Algorithms for Minimum-Load k-Facility Location
We consider a facility-location problem that abstracts settings where the cost of serving the clients assigned to a facility is incurred by the facility. Formally, we consider the minimum-load k-facility location (MLkFL) problem, which is defined as follows. We have a set F of facilities, a set C of clients, and an integer k ≥ 0. Assigning client j to a facility f incurs a connection cost d(f, ...
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We study the capacitated k-facility location problem, in which we are given a set of clients with demands, a set of facilities with capacities and a constant number k. It costs fi to open facility i, and cij for facility i to serve one unit of demand from client j. The objective is to open at most k facilities serving all the demands and satisfying the capacity constraints while minimizing the ...
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In this paper, some distributed approximation algorithms for uncapacitated facility location problem and fault-tolerant facility location problem are summarized, respectively. The worst-case run time of the distributed version of the uncapacitated facility location problem is ( ) O n , where n is the number of network nodes. In addition, the approximation approach for the fault-tolerant facilit...
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This paper surveys approximation algorithms for various facility location problems, mostly with detailed proofs. It resulted from lecture notes of a course held at the University of Bonn in the winter term 2004/2005.
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We present new approximation algorithms for several facility location problems. In each facility location problem that we study, there is a set of locations at which we may build a facility (such as a warehouse), where the cost of building at location i is fi; furthermore, there is a set of client locations (such as stores) that require to be serviced by a facility, and if a client at location ...
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ژورنال
عنوان ژورنال: ACM Transactions on Algorithms
سال: 2018
ISSN: 1549-6325,1549-6333
DOI: 10.1145/3173047