| Texto completo | |
| Autor(es): |
Morales, Davi Melo
;
Chaves, Antonio Augusto
;
Fazenda, Alvaro Luiz
;
IEEE
Número total de Autores: 4
|
| Tipo de documento: | Artigo Científico |
| Fonte: | 2018 IEEE INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM WORKSHOPS (IPDPSW 2018); v. N/A, p. 7-pg., 2019-01-01. |
| Resumo | |
The Clustering Search (CS) is a hybrid method that tries to combine metaheuristics and local search heuristics so that the search is intensified only in promising regions of the solution space. In this paper we propose a new parallel method based on the CS, using the Genetic Algorithm as a solutions generator, to solve the Capacitated Centered Clustering Problem (CCCP). The CCCP is to partition a set of n points into p disjoint groups with limited capacity. Each point is associated with a demand value and the objective is to minimize the sum of the Euclidean distances between the points and their respective geometric centers. The parallel CS consists in a master-slave system implemented following a message passing approach in order to parallelize the local search component, which is the most computationally demanding procedure. The computational results show that the parallel CS is an effective strategy in terms of computational time and efficiency. (AU) | |
| Processo FAPESP: | 15/24485-9 - Internet do futuro aplicada a cidades inteligentes |
| Beneficiário: | Fabio Kon |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |
| Processo FAPESP: | 12/17523-3 - Novos métodos híbridos para resolução de problemas de otimização combinatória |
| Beneficiário: | Antônio Augusto Chaves |
| Modalidade de apoio: | Auxílio à Pesquisa - Jovens Pesquisadores |
| Processo FAPESP: | 14/50937-1 - INCT 2014: da Internet do Futuro |
| Beneficiário: | Fabio Kon |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |