Authors: Brimberg, Jack
Janićijević, Stefana
Mladenović, Nenad 
Urošević, Dragan 
Title: Solving the clique partitioning problem as a maximally diverse grouping problem
Journal: Optimization Letters
Volume: 11
Issue: 6
First page: 1123
Last page: 1135
Issue Date: 1-Aug-2017
Rank: M21
ISSN: 1862-4472
DOI: 10.1007/s11590-015-0869-4
Abstract: 
In this paper we show that the clique partitioning problem can be reformulated in an equivalent form as the maximally diverse grouping problem (MDGP). We then modify a skewed general variable neighborhood search (SGVNS) heuristic that was first developed to solve the MDGP. Similarly as with the MDGP, significant improvements over the state of the art are obtained when SGVNS is tested on large scale instances. This further confirms the usefulness of a combined approach of diversification afforded with skewed VNS and intensification afforded with the local search in general VNS.
Keywords: Clique partitioning | Maximum diverse grouping problem | Variable neighborhood search
Project: Natural Sciences and Engineering Research Council of Canada Discovery Grant (NSERC #205041-2008)
Mathematical Modelas and Optimization Methods on Large-Scale Systems 
RSF (Russian Federation) grant 14-41-00039

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