Abstract
The redundancy allocation problem (RAP) is an important reliability optimization problem and has been an active area for the past decades. In literature, most of these system reliability problems are considered in series-parallel where the reliability of each components is considered as a precise value. Generalized redundancy allocation problem (GRAP) extends RAP to a more realistic situation where the reliabilities of the components are stochastic in nature and the system can have a complex network structure, for example, its components are connected with each other neither in series nor in parallel but in some logical relationship. In this paper, we proposed a new formulation of GRAP where the reliability of each component is modeled as a random variable with unknown distributions and developed particle-swarm-based simulation optimization method (PSSO) to identify the optimal solution efficiently. An extensive numerical study verifies the effectiveness and efficiency in realistic settings.