Submission Title
358— Hybridization of Particle Swam Optimization and Pattern Search Algorithms With Application
Submission Type
Presentation
Start Date
4-22-2020
Abstract
We test three methods of hybridizing Particle Swarm Optimization (PSO) and Pattern Search (PS) to improve the global minima, speed, and robustness. All methods let PSO run first followed by PS. The first method lets PSO use a large number of particles for a limited number of iterations. The second method lets PSO run normally until tolerance is reached. The third method lets PSO run normally until the average particle distance from the global best location is within a threshold. Numerical results using non-differentiable test functions reveal that all three methods improve the global minima and robustness versus PSO, while the third method also improves speed versus PSO. The third hybrid method was also applied to a basin network optimization problem and outperformed PSO with filter method and Genetic Algorithm (GA) with implicit filtering.
Recommended Citation
Koessler, Eric, "358— Hybridization of Particle Swam Optimization and Pattern Search Algorithms With Application" (2020). GREAT Day Posters. 111.
https://knightscholar.geneseo.edu/great-day-symposium/great-day-2020/posters-2020/111
Included in
358— Hybridization of Particle Swam Optimization and Pattern Search Algorithms With Application
We test three methods of hybridizing Particle Swarm Optimization (PSO) and Pattern Search (PS) to improve the global minima, speed, and robustness. All methods let PSO run first followed by PS. The first method lets PSO use a large number of particles for a limited number of iterations. The second method lets PSO run normally until tolerance is reached. The third method lets PSO run normally until the average particle distance from the global best location is within a threshold. Numerical results using non-differentiable test functions reveal that all three methods improve the global minima and robustness versus PSO, while the third method also improves speed versus PSO. The third hybrid method was also applied to a basin network optimization problem and outperformed PSO with filter method and Genetic Algorithm (GA) with implicit filtering.
Comments
Faculty Sponsor: Dr. Ahmad Almomani
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