Particle Swarm Optimization Using Adaptive Mutation

Two new variants of particle swarm optimization (PSO) called AMPSO1 and AMPSO2 are proposed for global optimization problems. Both the algorithms use adaptive mutation using beta distribution. AMPSO1 mutates the personal best position of the swarm and AMPSO2, mutates the global best swarm position....

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Bibliographic Details
Published in2008 19th International Workshop on Database and Expert Systems Applications pp. 519 - 523
Main Authors Pant, M., Thangaraj, R., Abraham, A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2008
Subjects
adaptive mutation
Benchmark testing
distribution
Equations
Evolutionary computation
Evolutionary programming
Mathematical model
Optimization
Particle swarm optimization
Programming
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Summary:Two new variants of particle swarm optimization (PSO) called AMPSO1 and AMPSO2 are proposed for global optimization problems. Both the algorithms use adaptive mutation using beta distribution. AMPSO1 mutates the personal best position of the swarm and AMPSO2, mutates the global best swarm position. The performance of proposed algorithms is evaluated on twelve unconstrained test problems and three real life constrained problems taken from the field of electrical engineering. The numerical results show the competence of the proposed algorithms with respect some other contemporary techniques.
ISBN:9780769532998
0769532993
ISSN:1529-4188
DOI:10.1109/DEXA.2008.70