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Solving reliability redundancy allocation problems with orthogonal simplified swarm optimization
Conference paper

Solving reliability redundancy allocation problems with orthogonal simplified swarm optimization

Wei-Chang Yeh, Vera Yuk Ying Chung, Yun-Zhi Jiang and Xiangjian He
Proceedings of the International Joint Conference on Neural Networks, Vol.2015-September, 7280420
09/2015

Abstract

Mixed-integer nonlinear programming Redundancy allocation problem Reliability RRAP Simplified Swarm Optimization algorithm SSO Software Artificial Intelligence
This study applies a penalty guided strategy and the orthogonal array test (OA) based on the Simplified Swarm Optimization algorithm (SSO) to solve the reliability redundancy allocation problems (RRAP) in the series system, the series-parallel system, the complex (bridge) system, and the overspeed protection of gas turbine system. For several decades, the RRAP has been one of the most well known techniques. The maximization of system reliability, the number of redundant components, and the reliability of corresponding components in each subsystem have to be decided simultaneously with nonlinear constraints, acting as one difficulty for the use of the RRAP. In other words, the objective function of the RRAP is the mixed-integer programming problem with the nonlinear constraints. The RRAP is of the class of NP-hard. Hence, in this paper, the SSO algorithm is proposed to solve the RRAP and improve computation efficiency for these NP-hard problems. There are four RRAP problems used to illustrate the applicability and the effectiveness of the SSO. The experimental results are compared with previously developed algorithms in literature. Moreover, the maximum-possible-improvement (MPI) is used to measure the amount of improvement of the solution found by the SSO to the previous solutions. According to the results, the system reliabilities obtained by the proposed SSO for the four RRAP problems are as well as or better than the previously best-known solutions.

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