NDLI: Bee colonies as model for multimodal continuous optimization: The OptBees algorithm

Content Provider	IEEE Xplore Digital Library
Author	Maia, R.D. de Castro, L.N. Caminhas, W.M.
Copyright Year	2012
Description	Author affiliation: Department of Computer Science, State University of Montes Claros, Brazil (Maia, R.D.) \|\| Natural Computing Laboratory (LCoN), Faculty of Electrical Engineering and Computer Science, Mackenzie University, São Paulo, Brazil (de Castro, L.N.) \|\| Computational Intelligence Laboratory, Department of Electronic Engineering, Federal University of Minas Gerais, Belo Horizonte, Brazil (Caminhas, W.M.)
Abstract	This paper presents the OptBees, an optimization algorithm inspired by the processes of collective decision-making by bee colonies. The algorithm was designed with the objective of generating and maintaining diversity, promoting a multimodal search and obtaining multiple local optima without losing the ability of global optimization, thus representing an innovation compared with existent bee-inspired algorithms. It has been tested in five of the twenty-five minimization problems proposed for the Optimization Competition of Real Parameters of the CEC 2005 Special Session on Real-Parameter Optimization, held in the 2005 IEEE Congress on Evolutionary Computation (CEC). The results obtained suggest the suitability of the algorithm to exploit multimodality of problems, being successful in the generation and maintenance of diversity and achieving good quality results in global optimization.
Starting Page	1
Ending Page	8
File Size	2229047
Page Count	8
File Format	PDF
ISBN	9781467315104
e-ISBN	9781467315098
e-ISBN	9781467315081
DOI	10.1109/CEC.2012.6252975
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-10
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Optimization Insects Recruitment Decision making Search problems Mathematical model Computational modeling diversity sociobiology insects bees collective decision-making optimization multimodality
Content Type	Text
Resource Type	Article

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