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OALib Journal期刊
ISSN: 2333-9721
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Personal Best Position Particle Swarm Optimization

Keywords: Standard Particle Swarm Optimization , SPSO , , PBPPSO , Personal Best Position Particle Swarm Optimization , Gbest , Global Best Position , Pbest , Personal Best Position , Current Position

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Abstract:

In this paper, a new particle swarm optimization method has been proposed. In the proposed approach a novel philosophy of modifying the velocity update equation of Standard Particle Swarm Optimization approach has been used. The modification has been done by vanishing the best term in the velocity update equation of SPSO. The performance of the proposed algorithm (Personal Best Position Particle Swarm Optimization, PBPPSO) has been tested on several benchmark problems. It is concluded that the PBPPSO performs better than SPSO in terms of accuracy and quality of solution

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