期刊
OPTIMIZATION LETTERS
卷 11, 期 6, 页码 1123-1135出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s11590-015-0869-4
关键词
Clique partitioning; Maximum diverse grouping problem; Variable neighborhood search
资金
- Natural Sciences and Engineering Research Council of Canada (NSERC) [205041-2008]
- Serbian Ministry of Sciences [174010]
- RSF (Russian Federation) [14-41-00039]
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.
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