A note on spare parts and logistic optimization with Monte Carlo based system models

The spare parts allocation is of primary importance for modern complex industrial and defense systems due to strong impact on the system performance and significant amount of resources invested in procurement and management of the inventory each year. These systems almost always involve complex operational aspects which require the use of the Monte Carlo (MC) method in order to model and analyze them. However, while the MC method enables realistic and reliable models analysis, it may not be sufficient for performing spare parts allocation optimization since it requires a substantial computer effort. A new and novel approach to this problem is presented in this paper. It is based on a new theorem, referred to as the "logistic optimization theorem ", and a hybrid MC/analytical approach and enables the construction of a new algorithm for a rigorous and practical optimization mechanism. The new method, which is explained in details, is verified and validated using a worked out example with a detailed comparison to the results achieved by other commonly used optimization methods.