 A hybrid metaheuristic method for the Maximum Diversity ProblemQinghua Wu and Jin-Kao Hao European Journal of Operational Research, 2013, vol. 231, issue 2, 452-464 Abstract: The Maximum Diversity Problem (MDP) consists in selecting a subset of m elements from a given set of n elements (n>m) in such a way that the sum of the pairwise distances between the m chosen elements is maximized. We present a hybrid metaheuristic algorithm (denoted by MAMDP) for MDP. The algorithm uses a dedicated crossover operator to generate new solutions and a constrained neighborhood tabu search procedure for local optimization. MAMDP applies also a distance-and-quality based replacement strategy to maintain population diversity. Extensive evaluations on a large set of 120 benchmark instances show that the proposed approach competes very favorably with the current state-of-art methods for MDP. In particular, it consistently and easily attains all the best known lower bounds and yields improved lower bounds for 6 large MDP instances. The key components of MAMDP are analyzed to shed light on their influence on the performance of the algorithm. Keywords: Maximum Diversity Problem; Solution combination; Local search; Constrained neighborhood; Population diversity (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:231:y:2013:i:2:p:452-464 DOI: 10.1016/j.ejor.2013.06.002 Access Statistics for this article European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati More articles in European Journal of Operational Research from Elsevier |
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