A Modified PSO Algorithm for Numerical Optimization Problems
| Autor: | Ching-Hai Lin, Jeun-Len Wu, Hsin-Chuan Kuo |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Numerical Analysis
Mathematical optimization education.field_of_study Optimization problem Applied Mathematics Population Particle swarm optimization Interval (mathematics) Computer Science Applications Exact solutions in general relativity Computational Theory and Mathematics Benchmark (computing) education Global optimization Analysis Premature convergence Mathematics |
| Zdroj: | Applied Mathematics & Information Sciences. 7:1229-1234 |
| ISSN: | 2325-0399 1935-0090 |
| DOI: | 10.12785/amis/070347 |
| Popis: | By successively employing the interval search method, we developed the proposed algorithm MPSO, introducing three creative position vectors to replace the three worst fitness particles among the population in the PSO, to overcome the premature convergence situation that occurs when a problem with a large number of variables and (or) multiple optima is solved. The results obtained by applying the MPSO and the PSO on 6 benchmark functions show that, except for the randomly shifted Rosenbrock functions, the MPSO can successfully secure a solution that is close to the exact solution for each of the remaining five functions. We also showed that all benchmark functions are solvable by the MPSO if the maximum number of generations is raised to be as high as possible. With regard to the PSOs performance for the three different numbers of variables, it fails to obtain a solution that is close to the exact solution for all of the tested functions except for the Sphere function with 30 variables. |
| Databáze: | OpenAIRE |
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