Memetic algorithm to optimize level of repair and spare part decisions for fleet system

摘要

The Level of Repair Analysis (LORA) and Spare Parts Provisioning (SPP) are the major maintenance planning decisions which have a direct impact on the Life Cycle Cost (LCC) of a capital intensive system. Such capital intensive systems are comprised of a considerable number of assemblies/sub-assemblies, which need to undergo optimized maintenance actions, proving to be beneficial for them. Employing heuristic methods can yield faster results which can converge to the global optimum. This research consists of an integrated approach which simultaneously optimizes the level of repair and spare parts decisions for fleet systems. This study uses the memetic algorithm to yield appropriate results for this complex combinatorial problem. It also draws a comparison of the results obtained by the memetic algorithm with those obtained by genetic algorithm.