Cluster analysis and mathematical programming

Cluster analysis and mathematical programming

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Article ID: iaor1999910
Country: Netherlands
Volume: 79
Issue: 13
Start Page Number: 191
End Page Number: 215
Publication Date: Oct 1997
Journal: Mathematical Programming
Authors: ,
Keywords: heuristics
Abstract:

Given a set of entities, Cluster Analysis aims at finding subsets, called clusters, which are homogeneous and/or well separated. As many types of clustering and criteria for homogeneity or separation are of interest, this is a vast field. A survey is given from a mathematical programming viewpoint. Steps of a clustering study, types of clustering and criteria are discussed. Then algorithms for hierarchical, partitioning, sequential, and additive clustering are studied. Emphasis is on solution methods, i.e. dynamic programming, graph theoretical algorithms, branch-and-bound, cutting planes, column generation and heuristics.

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