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Incremental algorithms for facility location and kmedian
 In Proceedings of the 12th Annual European Symposium on Algorithms, volume 3221 of Lecture Notes Comput. Sci
, 2004
"... In the incremental versions of Facility Location and kMedian, the demand points arrive one at a time and the algorithm maintains a good solution by either adding each new demand to an existing cluster or placing it in a new singleton cluster. The algorithm can also merge some of the existing cluste ..."
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Cited by 8 (0 self)
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In the incremental versions of Facility Location and kMedian, the demand points arrive one at a time and the algorithm maintains a good solution by either adding each new demand to an existing cluster or placing it in a new singleton cluster. The algorithm can also merge some of the existing
Approximation algorithms for metric facility location and kmedian problems using the . . .
"... ..."
Improved Combinatorial Algorithms for the Facility Location and kMedian Problems
 In Proceedings of the 40th Annual IEEE Symposium on Foundations of Computer Science
, 1999
"... We present improved combinatorial approximation algorithms for the uncapacitated facility location and kmedian problems. Two central ideas in most of our results are cost scaling and greedy improvement. We present a simple greedy local search algorithm which achieves an approximation ratio of 2:414 ..."
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Cited by 227 (11 self)
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We present improved combinatorial approximation algorithms for the uncapacitated facility location and kmedian problems. Two central ideas in most of our results are cost scaling and greedy improvement. We present a simple greedy local search algorithm which achieves an approximation ratio of 2
KMedians, Facility Location, and the ChernoffWald Bound
, 2000
"... We study the general (nonmetric) facilitylocation and weighted kmedians problems, as well as the fractional facilitylocation and unweighted kmedians problems. We describe a natural randomized rounding scheme and use it to derive approximation algorithms for all of these problems. For facility l ..."
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Cited by 9 (4 self)
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We study the general (nonmetric) facilitylocation and weighted kmedians problems, as well as the fractional facilitylocation and unweighted kmedians problems. We describe a natural randomized rounding scheme and use it to derive approximation algorithms for all of these problems. For facility
KMedians, Facility Location, and the ChernoffWald Bound
, 2002
"... We study the general (nonmetric) facilitylocation and weighted kmedians problems, as well as the fractional facilitylocation and kmedians problems. We describe a natural randomized rounding scheme and use it to derive approximation algorithms for all of these problems. For facility location and ..."
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We study the general (nonmetric) facilitylocation and weighted kmedians problems, as well as the fractional facilitylocation and kmedians problems. We describe a natural randomized rounding scheme and use it to derive approximation algorithms for all of these problems. For facility location
Continuous Weber and kMedian Problems
, 2000
"... We give the first exact algorithmic study of facility location problems that deal with finding a median for a continuum of demand points. In particular, we consider versions of the "continuous kmedian (Weber) problem" where the goal is to select one or more center points that minimize the ..."
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Cited by 16 (2 self)
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We give the first exact algorithmic study of facility location problems that deal with finding a median for a continuum of demand points. In particular, we consider versions of the "continuous kmedian (Weber) problem" where the goal is to select one or more center points that minimize
Planning Algorithms
, 2004
"... This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning, planning ..."
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Cited by 1108 (51 self)
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This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning
The Cricket LocationSupport System
, 2000
"... This paper presents the design, implementation, and evaluation of Cricket, a locationsupport system for inbuilding, mobile, locationdependent applications. It allows applications running on mobile and static nodes to learn their physical location by using listeners that hear and analyze informatio ..."
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Cited by 1036 (11 self)
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This paper presents the design, implementation, and evaluation of Cricket, a locationsupport system for inbuilding, mobile, locationdependent applications. It allows applications running on mobile and static nodes to learn their physical location by using listeners that hear and analyze
The reverse greedy algorithm for the metric kmedian problem
 Information Processing Letters
"... The Reverse Greedy algorithm (RGreedy) for the kmedian problem works as follows. It starts by placing facilities on all nodes. At each step, it removes a facility to minimize the total distance to the remaining facilities. It stops when k facilities remain. We prove that, if the distance function i ..."
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Cited by 7 (0 self)
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The Reverse Greedy algorithm (RGreedy) for the kmedian problem works as follows. It starts by placing facilities on all nodes. At each step, it removes a facility to minimize the total distance to the remaining facilities. It stops when k facilities remain. We prove that, if the distance function
Results 1  10
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73,338