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Comparing local search metaheuristics for the maximum diversity problem / Aringhier, R. in Journal of the operational research society (JORS), Vol. 62 N° 2 Special issue (Fevrier 2011) 

Public ISBD [article]  in Journal of the operational research society (JORS) > Vol. 62 N° 2 Special issue (Fevrier 2011) . - pp. 266–280 Titre : Comparing local search metaheuristics for the maximum diversity problem Type de document : texte imprimé Auteurs : Aringhier, R., Auteur ; Cordone, R., Auteur Année de publication : 2011 Article en page(s) : pp. 266–280 Note générale : Recherche opérationnelle Langues : Anglais (eng) Mots-clés : Maximum  diversity  problem  Tabu  search  Scatter  scarch  Variable  neighbourhood  search  Random  restart  comparisons Index. décimale : 001.424 Résumé : The Maximum Diversity Problem (MDP) requires to extract a subset M of given cardinality from a set N, maximising the sum of the pair-wise diversities between the extracted elements. The MDP has recently been the subject of much research, and several sophisticated heuristics have been proposed to solve it. The present work compares four local search metaheuristics for the MDP, all based on the same Tabu Search procedure, with the aim to identify what additional elements provide the strongest improvement. The four metaheuristics are an Exploring Tabu Search, a Scatter Search, a Variable Neighbourhood Search and a simple Random Restart algorithm. All of them prove competitive with the best algorithms proposed in the literature. Quite surprisingly, the best ones are the simple Random Restart algorithm and a Variable Neighbourhood Search algorithm with an unusual parameter setting, which makes it quite close to random restart. Although this is probably related to the elementary structure of the MDP, it also suggests that, more often than expected, simpler algorithms might be better. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n2/abs/jors2010104a.html [article] Comparing local search metaheuristics for the maximum diversity problem [texte imprimé] / Aringhier, R., Auteur ; Cordone, R., Auteur . - 2011 . - pp. 266–280. Recherche opérationnelle Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 62 N° 2 Special issue (Fevrier 2011) . - pp. 266–280 Mots-clés : Maximum  diversity  problem  Tabu  search  Scatter  scarch  Variable  neighbourhood  search  Random  restart  comparisons Index. décimale : 001.424 Résumé : The Maximum Diversity Problem (MDP) requires to extract a subset M of given cardinality from a set N, maximising the sum of the pair-wise diversities between the extracted elements. The MDP has recently been the subject of much research, and several sophisticated heuristics have been proposed to solve it. The present work compares four local search metaheuristics for the MDP, all based on the same Tabu Search procedure, with the aim to identify what additional elements provide the strongest improvement. The four metaheuristics are an Exploring Tabu Search, a Scatter Search, a Variable Neighbourhood Search and a simple Random Restart algorithm. All of them prove competitive with the best algorithms proposed in the literature. Quite surprisingly, the best ones are the simple Random Restart algorithm and a Variable Neighbourhood Search algorithm with an unusual parameter setting, which makes it quite close to random restart. Although this is probably related to the elementary structure of the MDP, it also suggests that, more often than expected, simpler algorithms might be better. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n2/abs/jors2010104a.html