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A novel adaptive sequential niche technique for multimodal function optimization
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DOI：10.1016/j.neucom.2006.02.016.png)
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Abstract
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This paper proposes a novel adaptive sequential niche particle swarm optimization (ASNPSO) algorithm, which uses multiple subswarms to detect optimal solutions sequentially. In this algorithm, the hill valley function is used to determine how to change the fitness of a particle in a sub-swarm run currently. This algorithm has strong and adaptive searching ability. The experimental results show that the proposed ASNPSO algorithm is very effective and efficient in searching for multiple optimal solutions for benchmark test functions without any prior knowledge. (c) 2006 Elsevier B.V. All rights reserved.
Keywords:
genetic algorithm
niche technique
particle swarm optimization
penalty function
Multimodal function optimization
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