Penalty guided PSO for reliability design problems

Authors:
Ta-Cheng Chen
Affiliations:
Department of Information Management, National Formosa University, Yulin, Taiwan
Venue:
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Year:
2006

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Abstract

This paper considers nonlinearly mixed integer reliability design problems in which both the number of redundancy components and the corresponding reliability of each component in each subsystem are to be decided simultaneously so as to maximize the system reliability. The reliability design problems have been studied in the literature for decades, usually using mathematical programming or heuristic/metaheuristic optimization approaches. The difficulties encountered for both methodologies are to maintain feasibility with respect to three nonlinear constraints, namely, cost and weight constraints, and constraints on the products of volume and weight. A penalty-guided particle swarm optimization approach is presented for solving the mixed integer reliability design problems. It can efficiently and effectively search over promising feasible and infeasible regions to find the feasible optimal or near optimal solution. Numerical examples indicate that the proposed approach performs better than other approaches for four reliability-redundant allocation design problems considered in this paper.