A Modified Particle Swarm Optimizer Algorithm
Yang Guangyou
Hubei University of Technology
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摘要与影响
This paper presented a modified particle swarm optimizer algorithm (MPSO). The aggregation degree of the particle swarm was introduced. The particles' diversity was improved through periodically monitoring aggregation degree of the particle swarm. On the later development of the PSO algorithm, it has been taken strategy of the Gaussian mutation to the best particle's position, which enhanced the particles' capacity to jump out of local minima. Several typical benchmark functions with different dimensions have been used for testing. The simulation results show that the proposed method improves the convergence precision and speed of PSO algorithm effectively.
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计算机 / AIMetaheuristic Optimization Algorithms Research
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