Quantum Behaved Particle Swarm Optimization Algorithm Based on Artificial Fish Swarm
| Autor: | Dong Yumin, Zhao Li |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Mathematical optimization
Meta-optimization Article Subject lcsh:Mathematics General Mathematics ComputingMethodologies_MISCELLANEOUS Computer Science::Neural and Evolutionary Computation MathematicsofComputing_NUMERICALANALYSIS General Engineering Particle swarm optimization Swarm behaviour lcsh:QA1-939 lcsh:TA1-2040 Derivative-free optimization Firefly algorithm Multi-swarm optimization lcsh:Engineering (General). Civil engineering (General) Metaheuristic Algorithm Mathematics Premature convergence |
| Zdroj: | Mathematical Problems in Engineering, Vol 2014 (2014) |
| ISSN: | 1563-5147 1024-123X |
| Popis: | Quantum behaved particle swarm algorithm is a new intelligent optimization algorithm; the algorithm has less parameters and is easily implemented. In view of the existing quantum behaved particle swarm optimization algorithm for the premature convergence problem, put forward a quantum particle swarm optimization algorithm based on artificial fish swarm. The new algorithm based on quantum behaved particle swarm algorithm, introducing the swarm and following activities, meanwhile using the adaptive parameters, to avoid it falling into local extremum of population. The experimental results show the improved algorithm to improve the optimization ability of the algorithm. |
| Databáze: | OpenAIRE |
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