One-half approximation algorithms for the k-partition problem
Operations Research - Supplement
SIAM Journal on Discrete Mathematics
Approximation algorithms for maximum dispersion
Operations Research Letters
Approximation algorithms for the metric maximum clustering problem with given cluster sizes
Operations Research Letters
On the Maximum Quadratic Assignment Problem
Mathematics of Operations Research
| Hi-index | 0.89 |
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 c1,...,cp. The goal is to find a partition of V into disjoint clusters of sizes c1,...,cp, maximizing the sum of weights of edges whose two ends belong to the same cluster. We describe an approximation algorithms for this problem with performance guarantee that approaches 0.5 when the cluster sizes are large.