Memetic particle swarm optimization
| Autor: | Michael N. Vrahatis, Y. G. Petalas, Konstantinos E. Parsopoulos |
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| Rok vydání: | 2007 |
| Předmět: |
Mathematical optimization
Meta-optimization business.industry Computer science ComputingMethodologies_MISCELLANEOUS Computer Science::Neural and Evolutionary Computation MathematicsofComputing_NUMERICALANALYSIS General Decision Sciences Particle swarm optimization Management Science and Operations Research Minimax ComputingMethodologies_ARTIFICIALINTELLIGENCE Derivative-free optimization Memetic algorithm Local search (optimization) Multi-swarm optimization business Metaheuristic Integer programming Global optimization |
| Zdroj: | Annals of Operations Research. 156:99-127 |
| ISSN: | 1572-9338 0254-5330 |
| DOI: | 10.1007/s10479-007-0224-y |
| Popis: | We propose a new Memetic Particle Swarm Optimization scheme that incorporates local search techniques in the standard Particle Swarm Optimization algorithm, resulting in an efficient and effective optimization method, which is analyzed theoretically. The proposed algorithm is applied to different unconstrained, constrained, minimax and integer programming problems and the obtained results are compared to that of the global and local variants of Particle Swarm Optimization, justifying the superiority of the memetic approach. |
| Databáze: | OpenAIRE |
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