| Full text | |
| Author(s): |
Morales, Davi Melo
;
Chaves, Antonio Augusto
;
Fazenda, Alvaro Luiz
;
IEEE
Total Authors: 4
|
| Document type: | Journal article |
| Source: | 2018 IEEE INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM WORKSHOPS (IPDPSW 2018); v. N/A, p. 7-pg., 2019-01-01. |
| Abstract | |
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) | |
| FAPESP's process: | 15/24485-9 - Future internet for smart cities |
| Grantee: | Fabio Kon |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 12/17523-3 - New hybrid methods to resolve combinatorial optimization problems |
| Grantee: | Antônio Augusto Chaves |
| Support Opportunities: | Research Grants - Young Investigators Grants |
| FAPESP's process: | 14/50937-1 - INCT 2014: on the Internet of the Future |
| Grantee: | Fabio Kon |
| Support Opportunities: | Research Projects - Thematic Grants |