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The Distribution-Free Newsboy Problem with Multiple Discounts and Upgrades

机译:具有多个折扣和升级的无分发报童问题

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摘要

Most papers on the newsboy problem assume that excess inventory is either sold after discount or discarded. In the real world, overstocks are handled with multiple discounts, upgrades, or a combination of these measures. For example, a seller may offer a series of progressively increasing discounts for units that remain on the shelf, or the seller may use incrementally applied innovations aimed at stimulating greater product sophistication. Moreover, the normal distribution does not provide better protection than other distributions with the same mean and variance. In this paper, we find the differences between normal distribution approaches and distribution-free approaches in four scenarios with mean and variance of demand as the only available data to decision-makers. First, we solve the newsboy problem by considering multiple discounts. Second, we formulate and solve the newsboy problem by considering multiple upgrades. Third, we formulate and solve a mixed newsboy problem characterized with multiple discounts and upgrades. Finally, we extend the model to solve a multiproduct newsboy problem with a storage or a budget constraint and develop an algorithm to find the solutions of the models. Concavity of the models is proved analytically. Extensive computational experiments are presented to verify the robustness of the distribution-free approach. The results show that the distribution-free approach is robust.
机译:关于报童问题的大多数论文都假定多余的存货要么折价出售要么丢弃。在现实世界中,库存积压是以多种折扣,升级或这些措施的组合来处理的。例如,卖方可以为保留在货架上的商品提供一系列逐步增加的折扣,或者卖方可以使用旨在刺激产品复杂性的增量应用创新。而且,正态分布不能提供比均值和方差相同的其他分布更好的保护。在本文中,我们发现正态分布方法与无分布方法在四种情况下的差异,需求均值和方差是决策者唯一可用的数据。首先,我们通过考虑多个折扣来解决报童问题。其次,我们通过考虑多次升级来制定和解决报童问题。第三,我们制定并解决带有多个折扣和升级的混合报童问题。最后,我们扩展模型以解决具有存储或预算约束的多产品报童问题,并开发一种算法来查找模型的解。分析证明了模型的凹性。进行了广泛的计算实验,以验证无分布方法的鲁棒性。结果表明,无分布方法是鲁棒的。

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  • 来源
    《Mathematical Problems in Engineering》 |2016年第9期|2017253.1-2017253.11|共11页
  • 作者单位

    Seoul Natl Univ, Dept Ind Engn, Seoul 08826, South Korea;

    LG Elect, Qual Management Dept, Seoul 07336, South Korea;

    Seoul Natl Univ, Dept Ind Engn, Seoul 08826, South Korea;

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