Title :
SelfAdaptive Bacteria Swarm for Optimization
Author :
Muoz, M.A. ; Lopez, Jesus A. ; Caicedo, Eduardo F.
Author_Institution :
Grupo de Investig. Perception y Sist. Inteligentes, Univ. del Valle, Cali
fDate :
Sept. 30 2008-Oct. 3 2008
Abstract :
This paper presents a self-adaptive bacteria swarm optimization algorithm, and its application in a suite of optimization benchmark problems, where the self-adaptive algorithm outperformed in most cases the non adaptive version. The algorithm follows a methodology that uses some concepts included in the evolution strategies for the parameter control, allowing the algorithm to select online the best parameter set.
Keywords :
biology; microorganisms; particle swarm optimisation; set theory; best parameter set; evolution strategies; self-adaptive bacteria swarm; swarm optimization algorithm; Adaptive control; Ant colony optimization; Automotive engineering; Educational institutions; Marine animals; Microorganisms; Particle swarm optimization; Programmable control; Robots; South America;
Conference_Titel :
Electronics, Robotics and Automotive Mechanics Conference, 2008. CERMA '08
Conference_Location :
Morelos
Print_ISBN :
978-0-7695-3320-9
DOI :
10.1109/CERMA.2008.97