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首页> 外文期刊>International journal of management science and engineering management >A newsboy problem for an inventory system under an emergency order: a modified invasive weed optimization algorithm
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A newsboy problem for an inventory system under an emergency order: a modified invasive weed optimization algorithm

机译：紧急命令下库存系统的报童问题：改进的侵入性杂草优化算法

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摘要

The newsboy problem has numerous applications for decision making in manufacturing and industrial environments. This paper presents a practical newsboy problem for an industrial system under both supplier quantity discounts and budget constraints where the storage space is stochastic and described using a normal distribution function. In this industrial system, when a shortage occurs, two strategies of the lost sale condition and the emergency order are available for the vendor as an option to fill the occurred shortage. This paper seeks to find the optimal order quantity for each product as well as to choose either the lost sale condition or the emergency order. The objective is to maximize the expected total profit of the vendor under uncertain demand and the stochastic storage space. As the proposed problem is NP-hard, a modified invasive weed optimization algorithm (IWO) is developed. The advantage of the proposed IWO is that it is capable of solving the proposed problem with both binary and continuous decision variables. As there is no benchmark available in the literature, an efficient genetic algorithm is designed to solve the problem and to compare the results obtained using IWO. Then, the algorithms are tuned using the response surface methodology and their performances are analyzed statistically. Finally, the applicability of the proposed approach and the solution methodologies are demonstrated. A sensitivity analysis on the number of products and discount segments indicates they have a significant impact on the vendor's tendency in choosing either the emergency order or the lost sale condition.
机译：报童问题在制造和工业环境中具有许多用于决策的应用程序。本文提出了一个在供应商数量折扣和预算约束下工业系统的报童问题，其中存储空间是随机的，并使用正态分布函数进行描述。在该工业系统中，当出现短缺时，卖方可以选择丢失销售状况和紧急订单的两种策略，以弥补发生的短缺。本文力求找到每种产品的最佳订单数量，并选择丢失的销售状况或紧急订单。目标是在不确定的需求和随机存储空间下最大化卖方的预期总利润。由于提出的问题是NP难的，因此开发了一种改进的侵入性杂草优化算法（IWO）。提出的IWO的优点在于，它能够用二进制和连续决策变量来解决提出的问题。由于文献中没有基准可用，因此设计了一种有效的遗传算法来解决该问题并比较使用IWO获得的结果。然后，使用响应面方法对算法进行调整，并对其性能进行统计分析。最后，证明了所提出的方法和解决方法的适用性。对产品和折扣部分数量的敏感性分析表明，它们对供应商选择紧急订单或失去销售条件的趋势有重大影响。

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