Improved Particle Swarm Optimization for Constrained Optimization
Автор: Zhicheng Qu, Qin Yang
Журнал: International Journal of Education and Management Engineering(IJEME) @ijeme
Статья в выпуске: 2 vol.2, 2012 года.
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In this paper, we present an improved particle swarm optimization (PSO) algorithm to solve constrained optimization problems. The proposed approach, called MPSO, employs a novel mutation operator to enhance the global search ability of PSO. In order to deal with constrains, MPSO uses mean violations mechanism and boundaries search. Simulation results on five famous benchmark problems show that MPSO achieves better results than standard PSO and another variant of PSO.
Particle swarm optimization (PSO), evolutionary computation, constranined optimization
Короткий адрес: https://sciup.org/15013656
IDR: 15013656
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