Simulation-based optimization for repairable systems using particle swarm algorithm

We describe an approach based on particle swarm optimization (PSO) for determining the optimal allocation of spares as well as repair resources while satisfying a desired availability constraint. The proposed method expands the original PSO algorithm to handle stochastic constraints and discrete decision variables. Computational results show that the proposed approach is efficient for determining the optimal choice of spares and repair channels for multi-echelon repairable-item inventory systems.