An adaptive particle swarm optimization method for multi-objective system reliability optimization

Mohamed Arezki Mellal and Enrico Zio

Journal of Risk and Reliability, 2019, vol. 233, issue 6, 990-1001

Abstract: 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, for example, maximize the reliability, minimize the cost, weight, and volume. In this article, an adaptive particle swarm optimization 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 particle swarm optimization.

Keywords: Multi-objective optimization; reliability–redundancy optimization; adaptive particle swarm optimization (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:sae:risrel:v:233:y:2019:i:6:p:990-1001

DOI: 10.1177/1748006X19852814

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