Improvements that use new formulae and strategies in particle swarm optimization (PSO) methods are proposed for updating the particles' velocity and position, craziness, and the use of simple refinement searching scheme and so on to enhance their performances. Numerical results are given to validate the feasibility and demonstrate the merits of the proposed method.
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