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A kind of hybrid optimization algorithm with prevention of premature convergence of particle swarm. (Chinese. English summary) Zbl 1174.68786
Summary: This paper treats a problem frequently appearing in Particle Swarm Optimization (PSO), premature convergence. A method, which selects particles stochastically to perform the conjugate gradient algorithm when the PSO stagnates, is proposed. Unlike the existing PSO algorithms, the presented method integrates the global search ability of the PSO and the powerful local search ability of the conjugate gradient algorithm. Thus, the problem of premature convergence of the PSO algorithm is solved. Simulation results show that the method has an improved performance for nonlinear functions of different dimension.
MSC:
68W20 Randomized algorithms
90C59 Approximation methods and heuristics in mathematical programming
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