Nonlinear crossing strategy-based particle swarm optimizations with time-varying acceleration coefficients
Keigo Watanabe,
Xiongshi Xu
Abstract:In contemporary particle swarm optimization (PSO) algorithms, to efficiently explore global optimum solutions, it is common practice to set the inertia weight to monotonically decrease over time for stability, while allowing the two acceleration coefficients, representing cognitive and social factors, to adopt decreasing or increasing functions over time, including random variations. However, there has been little discussion on a unified design approach for these time-varying acceleration coefficients. This pa… Show more
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