Reliability Optimization of the System with Common Cause Failures Based on Importance Measures

Abstract

In industrial engineering, the reliability analysis, modeling and optimization for complex systems are very important. Although the works about reliability optimization with the traditional method are numerous, researchers still study more efficient and accurate methods to solve these reliability problems. The common cause failures are the multiple failures with a common cause, which is typical and serious in practical systems. Therefore, on the basis of normal optimization methods of system reliability, this paper proposes an optimization method of system with common cause failures based on importance measures. The optimization models of parallel system and the series-parallel system are built and are solved with hybrid genetic algorithm. By analyzing the system reliability and cost increasing, the proposed method gives the more accurate, valid and robust optimization results. Meanwhile, the method provides an idea for the reliability optimization of multistate systems.