An entropy-based three-stage approach for multi-objective system reliability optimization considering uncertainty. Issue 9 (2nd September 2018)

• Record Type: Journal Article
• Authors: Cao, Ran; Hou, Wei; Gao, Yanying
• Is Part Of: Engineering optimization. Volume 50:Issue 9(2018)
• Page Start: 1453
• Page End: 1469
• Publication Date: 2018-09-02
• Subjects: Uncertainty -- entropy -- system reliability -- multi-objective optimization; Engineering design -- Periodicals; Mathematical optimization -- Periodicals; 620.0042
• DOI: 10.1080/0305215X.2017.1402014
• Languages: English
• ISSNs: 0305-215X

Abstract

ABSTRACT: This article presents a three-stage approach for solving multi-objective system reliability optimization problems considering uncertainty. The reliability of each component is considered in the formulation as a component reliability estimate in the form of an interval value and discrete values. Component reliability may vary owing to variations in the usage scenarios. Uncertainty is described by defining a set of usage scenarios. To address this problem, an entropy-based approach to the redundancy allocation problem is proposed in this study to identify the deterministic reliability of each component. In the second stage, a multi-objective evolutionary algorithm (MOEA) is applied to produce a Pareto-optimal solution set. A hybrid algorithm based on k -means and silhouettes is performed to select representative solutions in the third stage. Finally, a numerical example is presented to illustrate the performance of the proposed approach.