The particle swarm optimization algorithm is analyzed using standard results from the dynamic system theory. Graphical parameter selection guidelines are derived. The explorationβexploitation tradeoff is discussed and illustrated. Examples of performance on benchmark functions superior to previously
Parameter selection and adaptation in Unified Particle Swarm Optimization
β Scribed by K.E. Parsopoulos; M.N. Vrahatis
- Publisher
- Elsevier Science
- Year
- 2007
- Tongue
- English
- Weight
- 655 KB
- Volume
- 46
- Category
- Article
- ISSN
- 0895-7177
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β¦ Synopsis
The performance of the recently proposed Unified Particle Swarm Optimization method is investigated under different schemes for the determination and adaptation of the unification factor, which is the main parameter of the method, controlling its exploration and exploitation properties. Widely used benchmark problems are employed and numerous experiments are conducted along with statistical tests to yield useful conclusions regarding the effect of the parameter on the algorithm's performance as well as the most efficient adaptation schemes.
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