A cutting plane algorithm for a clustering problem
Mathematical Programming: Series A and B
Facets of the clique partitioning polytope
Mathematical Programming: Series A and B
Mathematical Programming: Series A and B
Mathematical Programming: Series A and B
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Modelling Robust Flight-Gate Scheduling as a Clique Partitioning Problem
Transportation Science
Cliques and clustering: A combinatorial approach
Operations Research Letters
Lagrangian relaxation and pegging test for the clique partitioning problem
Advances in Data Analysis and Classification
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This paper considers the problem of clustering the vertices of a complete edge-weighted graph. The objective is to maximize the sum of the edge weights within the clusters (also called cliques). This so-called Clique Partitioning Problem (CPP) is NP-complete, and has several real-life applications such as groupings in flexible manufacturing systems, in biology, in flight gate assignment, etc. Numerous heuristics and exact approaches as well as benchmark tests have been presented in the literature. Most exact methods use branch and bound with branching over edges. We present tighter upper bounds for each search tree node than those known from the literature, improve the constraint propagation techniques for fixing edges in each node, and present a new branching scheme. The theoretical improvements are reflected by computational tests with real-life data. Although a standard solver delivers best results on randomly generated data, the runtime of the proposed algorithm is very low when being applied to instances on object clustering.