Name
Abstract | ||
|---|---|---|
Clustering Search ((CS)-C-star) has been proposed as a generic way of combining search metaheuristics with clustering to detect promising search areas before applying local search procedures. The clustering process may keep representative solutions associated to different search subspaces (search areas). In this work, new approaches are proposed, based on Artificial Bee Colony (ABC) and Differential Evolution (DE), observing the inherent characteristics of detecting promising food sources employed by that metaheuristic. The proposed hybrid algorithms, performing a Hooke & Jeeves based local, are compared against another hybrid versions of ABC and DE, exploring an elitist criteria. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/CEC.2013.6557963 | 2013 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC) |
Keywords | Field | DocType |
differential evolution,tin,vectors,iron,abc,optimization,clustering algorithms,algorithm design and analysis,evolutionary computation | Mathematical optimization,Search algorithm,Guided Local Search,Correlation clustering,Computer science,Artificial intelligence,Local search (optimization),Cluster analysis,Machine learning,Tabu search,Best-first search,Metaheuristic | Conference |
Citations | PageRank | References |
0 | 0.34 | 10 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tarcísio Souza Costa | 1 | 17 | 2.24 |
| Alexandre César Muniz De Oliveira | 2 | 83 | 8.30 |