An optimum multiechelon repair policy and stockage model

A. Kaplan, D. Orr
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引用次数: 13

Abstract

Currently, sophisticated multiechelon models compute stockage quantities for spares and repair parts that will minimize total inventory investment while achieving a target level of weapon system operational availability. The maintenance policies to be followed are input to the stockage models. The Optimum Allocation of Test Equipment/Manpower Evaluated Against Logistics (OATMEAL) model will determine optimum maintenance as well as stockage policies for a weapon system. Specifically, it will determine at which echelon each maintenance function should be performed, including an option for component or module throwaway. Test equipment requirements to handle work load at each echelon are simultaneously optimized. Mixed-integer programming (MIP) combined with a Lagrangian approach are used to do the constrained cost minimization, that is, to minimize all costs dependent on maintenance and stockage policies while achieving a target weapons system operational availability. Real-life test cases are included.
最优多级维修策略及库存模型
目前,复杂的多层模型计算备件和维修部件的库存数量,将最大限度地减少总库存投资,同时实现武器系统操作可用性的目标水平。要遵循的维护策略被输入到存储模型中。测试设备/人力的优化分配(燕麦)模型将确定武器系统的最佳维护和储存政策。具体来说,它将确定每个维护功能应该在哪个梯队执行,包括组件或模块丢弃的选项。同时优化处理每个梯队工作负荷的测试设备要求。混合整数规划(MIP)与拉格朗日方法相结合,用于实现约束成本最小化,即在实现目标武器系统作战可用性的同时,最小化依赖于维护和储存策略的所有成本。包括现实生活中的测试用例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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