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Traditional inventory systems treat all demands of a given item equally. This approach is optimal if the penalty costs of all customers are the same, but it is not optimal if the penalty costs are different for different customer classes. Then, demands of customers with high penalty costs must be filled before demands of customers with low penalty costs. A commonly used inventory policy for dealing with demands with different penalty costs is the critical level inventory policy. Under this policy demands with low penalty costs are filled as long as inventory is above a certain critical level. If the inventory reaches the critical level, only demands with high penalty costs are filled and demands with low penalty costs are backordered. In this article, we consider a critical level policy for a periodic review inventory system with two demand classes. Because traditional approaches cannot be used to find the optimal parameters of the policy, we use a multidimensional Markov chain to model the inventory system. We use a sample path approach to prove several properties of this inventory system. Although the cost function is not convex, we can build on these properties to develop an optimization approach that finds the optimal solution. We also present some numerical results. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008 相似文献
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The optimization framework for optimal sensor placement for underwater threat detection has been developed. It considers single‐period and multiperiod detection models, each of which includes two components: detection algorithm and optimization problem for sensor placement. The detection algorithms for single‐period and multiperiod models are based on likelihood ratio and sequential testing, respectively. For the both models, the optimization problems use the principle of superadditive coverage, which is closely related to energy‐based and information‐based approaches. An algorithm for quasi‐regular sensor placement approximating solutions to the optimization problems has been developed based on corresponding continuous relaxations and a criterion for its applicability has been obtained. Numerical experiments have demonstrated that the algorithm consistently outperforms existing optimization techniques for optimal sensor placement.© 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008 相似文献
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随着“大智移云物”的出现和发展,战争形态已经发展到智能化战争新阶段。为了打赢未来智能化战争,推进军队财务管理实现智能化,充分利用军事大数据这一新兴重要战略资源尤为必要。本文利用需求分析法和现象分类法,从经费需求测算、预算编制、军费支出和军费绩效评估四个方面分析了军队财务管理领域应用军事大数据的需求。针对当前存在的运用军事大数据观念淡薄、数据采集困难、数据挖掘处理能力较弱、数据安全威胁及军事大数据人才缺乏等五个问题,从大数据应用观念的树立、软硬件设备的更新、数据中心的建设、应用框架的构建、信息化管理制度的完善、数据安全管理和大数据人才队伍建设几个方面提出了在军队财务管理领域应用军事大数据的思路。 相似文献