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首页> 外文期刊>The Kasetsart Journal >A Nonlinear Optimization Problem for Determining Safety Stocks in a Two-Stage Manufacturing System
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A Nonlinear Optimization Problem for Determining Safety Stocks in a Two-Stage Manufacturing System

机译：确定两阶段制造系统安全库存的非线性优化问题

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摘要

Safety stock is the inventory which is used to buffer against the uncertainties in business operations. Managers must decide how much safety stock of each raw material and each finished product should be maintained. Determining appropriate safety stock levels is an important decision. Too much safety stock would incur extra inventory carrying costs, whereas too less safety stock would increase the risk of having product stockouts and lost sales. In this paper, a nonlinear programming problem for determining safety stock levels in a two-stage manufacturing system, was presented. Instead of using the well-known search algorithms, simple decision rules for determining safety stock levels were derived from an analysis of the derivatives of cost functions, with respect to the delivery performances of suppliers and prior manufacturing process. Two algorithms based on those decision rules were proposed and tested on seventy-five problem instances. The results showed that the proposed algorithms provided, within 1 second, the solutions with less than 3% deviations, on average, from the known integer solutions or the best lower bounds. The algorithms also performed better than the pattern search algorithm, which was the method applied in the previous research.
机译：安全库存是用来缓冲业务运营中不确定性的库存。管理者必须决定应维持每种原材料和每种成品多少安全库存。确定适当的安全库存水平是一个重要的决定。安全库存过多会导致额外的库存携带成本，而安全库存太少则会增加产品缺货和销售损失的风险。本文提出了一种用于确定两阶段制造系统中安全库存水平的非线性规划问题。代替使用众所周知的搜索算法，从对供应商的交货性能和先前制造过程的成本函数导数的分析中得出用于确定安全库存水平的简单决策规则。提出了两种基于这些决策规则的算法，并在75个问题实例上进行了测试。结果表明，所提出的算法在1秒钟内提供了与已知整数解或最佳下限平均偏差小于3％的解。该算法的性能也优于先前研究中应用的模式搜索算法。

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