Paper Info
Title
Artificial bee clustering search
Abstract
Clustering Search (*CS) 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, a new approach is proposed, based on Artificial Bee Colony (ABC), observing the inherent characteristics of detecting promissing food sources employed by that metaheuristic. The proposed hybrid algorithm, performing a Hooke & Jeeves based local, is compared against other versions of ABC: a pure ABC and another hybrid ABC, exploring an elitist criteria.
Year
DOI
Venue
2013
10.1007/978-3-642-38682-4_3
IWANN (2)
Keywords
Field
DocType
clustering process,hybrid abc,proposed hybrid algorithm,artificial bee colony,search area,pure abc,local search procedure,promising search area,artificial bee,different search subspaces,search metaheuristics
Hybrid algorithm,Guided Local Search,Computer science,Linear subspace,Artificial intelligence,Local search (optimization),Cluster analysis,Machine learning,Metaheuristic
Conference
Volume
ISSN
Citations 
7903
0302-9743
0
PageRank 
References 
Authors
0.34
5
2
Name
Order
Citations
PageRank
Tarcísio Souza Costa1172.24
Alexandre César Muniz De Oliveira2838.30