An adaptive particle swarm optimization method for multi-objective system reliability optimization
Résumé
Multi-objective system reliability optimization has attracted the attention of several researchers, due to its importance in industry. In practice, the optimization regards multiple objectives, e.g., maximize the reliability, minimize the cost, weight and volume. In this paper, an adaptive particle swarm optimization (ADAP-PSO) is presented for multi-objective system reliability optimization. The approach uses a Lévy flight for some particles of the swarm, for avoiding local optima and insuring diversity in the exploration of the search space. The multi-objective problem is converted to a single-objective problem by resorting to the weighted-sum method and a penalty function is implemented to handle the constraints. Nine numerical case studies are presented as benchmark problems for comparison; the results show that the proposed approach has superior performance than a standard PSO.
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