An Efficient Simulation Optimization Method for the Generalized Redundancy Allocation Problem Under Uncertain Component Reliability

The redundancy allocation problem (RAP) is an important reliability optimization problem and has been an active area of research for the past decades. In the literature, most of these system reliability problems are considered in series–parallel where the reliability of each component is assumed a known constant. However, in reality, the component reliability may exhibit quality variations and the reliability of each component shall be better considered stochastic. This motivates this paper to extend the RAP to a more realistic situation in which the reliability of each component is stochastic in nature and the system can have a complex network structure, i.e., the system components are connected with each other neither in series nor in parallel but in some logical relationship. Due to the complex network structure and aggregated profound stochasticity, the overall system reliability is not analytically available but instead has to rely on simulation for estimation. We therefore develop a Particle-Swarm-based Simulation Optimization (PSSO) method to enable the optimal solution to be identified efficiently. An extensive numerical study verifies the efficacy and efficiency of our proposed method in realistic settings and is worth further investigation.