Approximation algorithms for the metric maximum clustering problem with given cluster sizes

被引：2
|
作者：
Hassin, R [1 ]
Rubinstein, S [1 ]
机构：
[1] Tel Aviv Univ, Sch Math Sci, Dept Stat & Operat Res, IL-69978 Tel Aviv, Israel
来源：
OPERATIONS RESEARCH LETTERS | 2003年 / 31卷 / 03期
关键词：
approximation algorithms; maximum clustering;
D O I：
10.1016/S0167-6377(02)00235-3
中图分类号：
C93 [管理学]; O22 [运筹学];
学科分类号：
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要：
The input to the METRIC MAXIMUM CLUSTERING PROBLEM WITH GIVEN CLUSTER SIZES consists of a complete graph G=(V, E) with edge weights satisfying the triangle inequality, and integers c(1),...., c(p) that sum to I V. The goal is to find a partition of V into disjoint clusters of sizes c(1),....,c(p), that maximizes the sum of weights of edges whose two ends belong to the same cluster. We describe approximation algorithms for this problem. (C) 2003 Elsevier Science B.V. All rights reserved.
引用
收藏
页码：179 / 184
页数：6
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