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作 者:王维娜[1,2,3] 孙林岩[1,2,3] 张盛浩[1] 王凌[1]
机构地区:[1]西安交通大学管理学院,陕西西安710049 [2]过程控制与效率工程教育部重点实验室,陕西西安710049 [3]机械制造系统国家重点实验室,陕西西安710049
出 处:《运筹与管理》2013年第5期217-225,共9页Operations Research and Management Science
基 金:国家自然科学基金项目(70901062);教育部高等学校博士学科点基金(200806981066);机械制造系统工程国家重点实验室青年基金项目
摘 要:本文研究一个周期性订货的多设备同备件库存系统,将备件库存策略与设备状态监控相结合,讨论了存在设备状态监控情形下的备件库存策略。针对设备状态自然腐蚀过程和人为修复过程的复合过程,运用一个新的马尔科夫概率转移矩阵对设备需求概率进行刻画,并在此基础上给出静态订货模型和状态监控下的动态订货模型的最优订货策略。通过对比以上两种订货策略优缺点,本文提出一种新的启发式订货策略:基于关键状态的订货策略模型。该策略可以有效降低对全部设备实行动态监控的信息成本,且成本节省优于静态订货策略,对于企业的现实问题有着较好的指导意义。In this paper, we study the replenishment strategies faced by enterprise spare parts management. To draw close to the actual condition, we combine the spare parts inventory strategies with equipment state monitoring by using a Markov process to model the probability of equipment' s requirement. We consider three models in this paper: a static base-stock inventory strategy ; dynamic base-stock inventory strategy with state monitoring and dynamic base-stock inventory strategy based on key state monitoring. Our conclusions show that the first two models can change to a newsvendor problem in some situation and we can sovle them by some optimization methods. Compared with the advantages and shortages of those two strategies, we provide a new heuristic strategy: dynamic base-stock inventory strategy based on key state monitoring. Results show that the shortage cost of dynamic ordering model under state monitoring is the lowest. But the new strategy can reduce the search cost to get all equipment' s state, and the new strategy is easier to use for companies.
分 类 号:O227[理学—运筹学与控制论]
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