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A Note on Spare Parts and Logistic Optimization with Monte Carlo based System Models
Volume 7, Number 5, September 2011 - Paper 1 - pp. 405-416
ARIE DUBI1, STANISLAV KHOROSHEVSKY2, and AVINOAM DORON11 Department of Nuclear Engineering,
2 Department of Industrial Engineering and Management,
Ben-Gurion University of the Negev, Beer Sheva, Israel
(Received on November 22, 2010 and revised on May 22, 2011)
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.
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