A new approach of midrange exploration exploitation searching particle swarm optimization for optimal solution
The conventional Particle Swarm Optimization (PSO) was introduced as an optimization technique for real applications such as image processing, tracking, localization, and scheduling. However, conventional PSO still has its limitation in finding optimal solutions and is always trapped in the local op...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2023
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/40315/1/A%20new%20approach%20of%20midrange%20exploration%20exploitation.pdf http://umpir.ump.edu.my/id/eprint/40315/2/A%20new%20approach%20of%20midrange%20exploration%20exploitation%20searching%20particle%20swarm%20%20optimization%20for%20optimal%20solution_ABS.pdf |
| Summary: | The conventional Particle Swarm Optimization (PSO) was introduced as an optimization technique for real applications such as image processing, tracking, localization, and scheduling. However, conventional PSO still has its limitation in finding optimal solutions and is always trapped in the local optima. Therefore, the concept of conventional PSO was unsuitable to be used in dynamic problems. In order to address these issues, we have introduced a novel enhancement approach known as Midrange Exploration Exploitation Searching Particle Swarm Optimization (MEESPSO) to categorize the particle into resident particles and migrant particles according to midrange value. A migrant particle will execute the process of exploration to other search spaces, meanwhile resident particles went through the process of exploitation accordingly to the best solution. The comparison result shows that MEESPSO has the talent to increase the accuracy in a real application. |
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