Abstract
A modified particle swarm optimization (MPSO) algorithm is proposed to solve reliability problems in this paper. The MPSO modifies the velocity updating of particle swarm optimization (PSO) algorithm. For each particle, its personal best particle and the global best particle are separated to update its velocity, in other words, either its personal best particle or the global best particle is considered for velocity updating, and it is determined by a dynamic probability. In addition, a new inertia weight is introduced into the velocity updating, and it is used to balance the global search and local search. Based on a large number of experiments, the proposed algorithm has demonstrated stronger convergence and stability than the other two PSO algorithms on solving reliability problems. The results show that the MPSO can be an efficient alternative for solving reliability problems.
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