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A Note on Spare Parts and Logistic Optimization with Monte Carlo based System Models

机译:关于基于蒙特卡洛系统模型的备件和物流优化的注记

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摘要

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.
机译:备件分配对于现代复杂的工业和国防系统而言至关重要,因为它会对系统性能产生重大影响,并且每年会花费大量资源来采购和管理库存。这些系统几乎总是涉及复杂的操作方面,因此需要使用蒙特卡洛(MC)方法进行建模和分析。但是,尽管MC方法可以进行现实可靠的模型分析,但由于执行这种方法需要大量的计算机工作,因此可能不足以执行备件分配优化。本文提出了一种解决该问题的新颖方法。它基于被称为“逻辑优化定理”的新定理和混合MC /分析方法,并为严格而实用的优化机制构建了新算法。将使用一个已举例说明的示例对新方法进行详细的验证和确认,并与其他常用优化方法所获得的结果进行详细比较。

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