| Titre : | A hybrid genetic algorithmic approach to the maximally diverse grouping problem (2011) |
| Auteurs : | Fan, Z. P., Auteur ; Y. Chen, Auteur ; Ma, J., Auteur |
| Type de document : | Article : texte imprimé |
| Dans : | Journal of the operational research society (JORS) (Vol. 62 N° 1, Janvier 2011) |
| Article en page(s) : | pp. 92–99 |
| Note générale : | Recherche opérationnelle |
| Langues : | Anglais |
| Index. décimale : | 001.424 |
| Tags : | Genetic algorithm Maximally diverse grouping problem Local neighbourhood search |
| 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 |
