Authors: Brimberg, Jack
Mladenović, Nenad 
Urošević, Dragan 
Affiliations: Mathematical Institute of the Serbian Academy of Sciences and Arts 
Title: Solving the maximally diverse grouping problem by skewed general variable neighborhood search
Journal: Information Sciences
Volume: 295
First page: 650
Last page: 675
Issue Date: 1-Jan-2015
Rank: M21a
ISSN: 0020-0255
DOI: 10.1016/j.ins.2014.10.043
The maximally diverse grouping problem requires finding a partition of a given set of elements into a fixed number of mutually disjoint subsets (or groups) in order to maximize the overall diversity between elements of the same group. In this paper we develop a new variant of variable neighborhood search for solving the problem. The extensive computational results show that our new heuristic significantly outperforms the current state of the art. Moreover, the best known solutions have been improved on 531 out of 540 test instances from the literature.
Keywords: Combinatorial optimization | General variable neighborhood search | Maximally diverse grouping problem | Skewed variable neighborhood search
Publisher: Elsevier
Project: Natural Sciences and Engineering Research Council of Canada Discovery Grant (NSERC # 205041-2008)
Mathematical Modelas and Optimization Methods on Large-Scale Systems 
Development of new information and communication technologies, based on advanced mathematical methods, with applications in medicine, telecommunications, power systems, protection of national heritage and education 
RSF (Russian Federation) grant 14-41-00039

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