Treffer: Facility location in sublinear time

Title:
Facility location in sublinear time
Source:
Automata, languages and programming (Lisbon, 11-15 July 2005)Lecture notes in computer science. :866-877
Publisher Information:
Berlin: Springer, 2005.
Publication Year:
2005
Physical Description:
print, 14 ref
Original Material:
INIST-CNRS
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
MIT Computer Science and Artificial Intelligence Laboratory, Stata Center, Cambridge, Massachusetts 02139, United States
Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102, United States
Heinz Nixdorf Institute and Computer Science Department, University of Paderborn, 33102 Paderborn, Germany
ISSN:
0302-9743
Rights:
Copyright 2005 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.16991849
Database:
PASCAL Archive

Weitere Informationen

In this paper we present a randomized constant factor approximation algorithm for the problem of computing the optimal cost of the metric Minimum Facility Location problem, in the case of uniform costs and uniform demands, and in which every point can open a facility. By exploiting the fact that we are approximating the optimal cost without computing an actual solution, we give the first algorithm for this problem with running time O(n log2 n), where n is the number of metric space points. Since the size of the representation of an n-point metric space is Θ(n2), the complexity of our algorithm is sublinear with respect to the input size. We consider also the general version of the metric Minimum Facility Location problem and we show that there is no o(n2)-time algorithm, even a randomized one, that approximates the optimal solution to within any factor. This result can be generalized to some related problems, and in particular, the cost of minimum-cost matching, the cost of bichromatic matching, or the cost of n/2-median cannot be approximated in o(n2)-time.