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A hybrid genetic algorithmic approach to the maximally diverse grouping problem / Fan, Z. P. in Journal of the operational research society (JORS), Vol. 62 N° 1 (Janvier 2011) 

Public ISBD [article]  in Journal of the operational research society (JORS) > Vol. 62 N° 1 (Janvier 2011) . - pp. 92–99 Titre : A hybrid genetic algorithmic approach to the maximally diverse grouping problem Type de document : texte imprimé Auteurs : Fan, Z. P., Auteur ; Y. Chen, Auteur ; Ma, J., Auteur Année de publication : 2011 Article en page(s) : pp. 92–99 Note générale : Recherche opérationnelle Langues : Anglais (eng) Mots-clés : Genetic  algorithm  Maximally  diverse  grouping  problem  Local  neighbourhood  search Index. décimale : 001.424 Résumé : The maximally diverse grouping problem (MDGP) is a NP-complete problem. For such NP-complete problems, heuristics play a major role in searching for solutions. Most of the heuristics for MDGP focus on the equal group-size situation. In this paper, we develop a genetic algorithm (GA)-based hybrid heuristic to solve this problem considering not only the equal group-size situation but also the different group-size situation. The performance of the algorithm is compared with the established Lotfi–Cerveny–Weitz algorithm and the non-hybrid GA. Computational experience indicates that the proposed GA-based hybrid algorithm is a good tool for solving MDGP. Moreover, it can be easily modified to solve other equivalent problems. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n1/abs/jors2009168a.html [article] A hybrid genetic algorithmic approach to the maximally diverse grouping problem [texte imprimé] / Fan, Z. P., Auteur ; Y. Chen, Auteur ; Ma, J., Auteur . - 2011 . - pp. 92–99. Recherche opérationnelle Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 62 N° 1 (Janvier 2011) . - pp. 92–99 Mots-clés : Genetic  algorithm  Maximally  diverse  grouping  problem  Local  neighbourhood  search Index. décimale : 001.424 Résumé : The maximally diverse grouping problem (MDGP) is a NP-complete problem. For such NP-complete problems, heuristics play a major role in searching for solutions. Most of the heuristics for MDGP focus on the equal group-size situation. In this paper, we develop a genetic algorithm (GA)-based hybrid heuristic to solve this problem considering not only the equal group-size situation but also the different group-size situation. The performance of the algorithm is compared with the established Lotfi–Cerveny–Weitz algorithm and the non-hybrid GA. Computational experience indicates that the proposed GA-based hybrid algorithm is a good tool for solving MDGP. Moreover, it can be easily modified to solve other equivalent problems. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n1/abs/jors2009168a.html

A hybrid genetic algorithmic approach to the maximally diverse grouping problem / Fan, Z. P. in Journal of the operational research society (JORS), Vol. 62 N° 7 (Juillet 2011) 

Public ISBD [article]  in Journal of the operational research society (JORS) > Vol. 62 N° 7 (Juillet 2011) . - pp. 1423–1430 Titre : A hybrid genetic algorithmic approach to the maximally diverse grouping problem Type de document : texte imprimé Auteurs : Fan, Z. P., Auteur ; Y. Chen, Auteur ; Ma, J., Auteur Année de publication : 2011 Article en page(s) : pp. 1423–1430 Note générale : Recherche opérationnelle Langues : Anglais (eng) Mots-clés : Genetic  algorithm  Maximally  diverse  grouping  problem  Local  neighbourhood  search Index. décimale : 001.424 Résumé : The maximally diverse grouping problem (MDGP) is a NP-complete problem. For such NP-complete problems, heuristics play a major role in searching for solutions. Most of the heuristics for MDGP focus on the equal group-size situation. In this paper, we develop a genetic algorithm (GA)-based hybrid heuristic to solve this problem considering not only the equal group-size situation but also the different group-size situation. The performance of the algorithm is compared with the established Lotfi–Cerveny–Weitz algorithm and the non-hybrid GA. Computational experience indicates that the proposed GA-based hybrid algorithm is a good tool for solving MDGP. Moreover, it can be easily modified to solve other equivalent problems. Note de contenu : Corrections to: Journal of the Operational Research Society (2010). doi:10.1057/jors.2009.168; published online 6 January 2010 DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n7/abs/jors201092a.html [article] A hybrid genetic algorithmic approach to the maximally diverse grouping problem [texte imprimé] / Fan, Z. P., Auteur ; Y. Chen, Auteur ; Ma, J., Auteur . - 2011 . - pp. 1423–1430. Recherche opérationnelle Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 62 N° 7 (Juillet 2011) . - pp. 1423–1430 Mots-clés : Genetic  algorithm  Maximally  diverse  grouping  problem  Local  neighbourhood  search Index. décimale : 001.424 Résumé : The maximally diverse grouping problem (MDGP) is a NP-complete problem. For such NP-complete problems, heuristics play a major role in searching for solutions. Most of the heuristics for MDGP focus on the equal group-size situation. In this paper, we develop a genetic algorithm (GA)-based hybrid heuristic to solve this problem considering not only the equal group-size situation but also the different group-size situation. The performance of the algorithm is compared with the established Lotfi–Cerveny–Weitz algorithm and the non-hybrid GA. Computational experience indicates that the proposed GA-based hybrid algorithm is a good tool for solving MDGP. Moreover, it can be easily modified to solve other equivalent problems. Note de contenu : Corrections to: Journal of the Operational Research Society (2010). doi:10.1057/jors.2009.168; published online 6 January 2010 DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v62/n7/abs/jors201092a.html