Results 1  10
of
318,091
KMedian Problem on Graph
"... In past decades there has been a tremendous growth in the literature on location problems. However, among the myriad of formulations provided, the simple plant location problem and the kmedian problem have played a centra l role. This phenomenon is due to the fact that both problems have a wide ran ..."
Abstract
 Add to MetaCart
In past decades there has been a tremendous growth in the literature on location problems. However, among the myriad of formulations provided, the simple plant location problem and the kmedian problem have played a centra l role. This phenomenon is due to the fact that both problems have a wide
The kMedian Problem for Directed Trees
, 2003
"... The kmedian problem is a classical facility location problem. We consider the kmedian problem for directed trees, motivated by the problem of locating proxies on the World Wide Web. The two main results of the paper are an O(n log n) time algorithm for k = 2 and an O(n log² n) time algorithm fo ..."
Abstract

Cited by 2 (1 self)
 Add to MetaCart
The kmedian problem is a classical facility location problem. We consider the kmedian problem for directed trees, motivated by the problem of locating proxies on the World Wide Web. The two main results of the paper are an O(n log n) time algorithm for k = 2 and an O(n log² n) time algorithm
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 ..."
Abstract

Cited by 16 (2 self)
 Add to MetaCart
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
Inapproximability of the Asymmetric Facility Location and kMedian Problems
, 2000
"... In the asymmetric versions of the uncapacitated facility location and kmedian problems, distances satisfy the triangle inequality but the distances from point i to point j and from j to i may di#er. For the facility location problem there is an O(log N) approximation algorithm due to Hochbaum. F ..."
Abstract

Cited by 12 (1 self)
 Add to MetaCart
In the asymmetric versions of the uncapacitated facility location and kmedian problems, distances satisfy the triangle inequality but the distances from point i to point j and from j to i may di#er. For the facility location problem there is an O(log N) approximation algorithm due to Hochbaum
Inapproximability of the Asymmetric Facility Location and kMedian Problems
, 2000
"... Abstract In the asymmetric versions of the uncapacitated facility location and kmedian problems,distances satisfy the triangle inequality but the distances from point i to point j and from j to i may differ. For the facility location problem there is an O(log N) approximation algorithmdue to Hochba ..."
Abstract
 Add to MetaCart
Abstract In the asymmetric versions of the uncapacitated facility location and kmedian problems,distances satisfy the triangle inequality but the distances from point i to point j and from j to i may differ. For the facility location problem there is an O(log N) approximation algorithmdue
An Efficient Local Search Algorithm for kMedian Problem
"... Abstract: The kmedian problem is one of the NPhard combinatorial optimization problems. It falls into the general class of clustering problem and has application in the field of classification and data mining. One has confirmed that local search technique is the most effective and simplest method ..."
Abstract
 Add to MetaCart
Abstract: The kmedian problem is one of the NPhard combinatorial optimization problems. It falls into the general class of clustering problem and has application in the field of classification and data mining. One has confirmed that local search technique is the most effective and simplest method
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 ..."
Abstract

Cited by 7 (0 self)
 Add to MetaCart
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
New Approximability Results for the Robust kMedian Problem
"... We consider a robust variant of the classical kmedian problem, introduced by Anthony et al. [2]. In the Robust kMedian problem, we are given an nvertex metric space (V, d) and m client sets {Si ⊆ V}mi=1. The objective is to open a set F ⊆ V of k facilities such that the worst case connection cost ..."
Abstract
 Add to MetaCart
We consider a robust variant of the classical kmedian problem, introduced by Anthony et al. [2]. In the Robust kMedian problem, we are given an nvertex metric space (V, d) and m client sets {Si ⊆ V}mi=1. The objective is to open a set F ⊆ V of k facilities such that the worst case connection
PROBI: A Heuristic for the probabilistic kmedian problem
, 2014
"... Abstract. We develop the heuristic PROBI for the probabilistic Euclidean kmedian problem based on a coreset construction by Lammersen et al. [28]. Our algorithm computes a summary of the data and then uses an adapted version of kmeans++ [5] to compute a good solution on the summary. The summary is ..."
Abstract
 Add to MetaCart
Abstract. We develop the heuristic PROBI for the probabilistic Euclidean kmedian problem based on a coreset construction by Lammersen et al. [28]. Our algorithm computes a summary of the data and then uses an adapted version of kmeans++ [5] to compute a good solution on the summary. The summary
A constantfactor approximation algorithm for the kmedian problem
 In Proceedings of the 31st Annual ACM Symposium on Theory of Computing
, 1999
"... We present the first constantfactor approximation algorithm for the metric kmedian problem. The kmedian problem is one of the most wellstudied clustering problems, i.e., those problems in which the aim is to partition a given set of points into clusters so that the points within a cluster are re ..."
Abstract

Cited by 252 (12 self)
 Add to MetaCart
We present the first constantfactor approximation algorithm for the metric kmedian problem. The kmedian problem is one of the most wellstudied clustering problems, i.e., those problems in which the aim is to partition a given set of points into clusters so that the points within a cluster
Results 1  10
of
318,091