Niche Artificial Fish Swarm Algorithm based on quantum theory

Artificial Fish Swarm Algorithm (AFSA) is a new swarm intelligence optimization algorithm which is designed to find the single optimal solution for a given problem. But in some practical applications, the global optimal solution and some near optimal solutions are both needed. So a novel Niche Quant...

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Bibliographic Details
Main Authors: Kongcun Zhu, Mingyan Jiang, Yongming Cheng
Format: Conference Proceeding
Language:English
Subjects:
AFSA
Algorithm design and analysis
Marine animals
niche
Optimization
Particle swarm optimization
Quantum computing
Quantum mechanics
quantum mechanism
RCS strategy
Signal processing algorithms
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Summary:Artificial Fish Swarm Algorithm (AFSA) is a new swarm intelligence optimization algorithm which is designed to find the single optimal solution for a given problem. But in some practical applications, the global optimal solution and some near optimal solutions are both needed. So a novel Niche Quantum Artificial Fish Swarm Algorithm (NQAFSA) is proposed in this paper to solve these problems. The quantum mechanism is introduced into the AFSA to increase the diversity of species. Artificial Fish (AF) are divided into several sub-swarms to form the niche and the restricted competition selection (RCS) strategy is used to maintain the niche. The performance of NQAFSA is validated by the experimental results.
ISSN:2164-5221
DOI:10.1109/ICOSP.2010.5656939