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Optimal information acquisition, inventory control, and forecast sharing in operations management.

机译:运营管理中的最佳信息获取,库存控制和预测共享。

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摘要

Efficient information acquisition and sharing is the key to unlocking latent values in many operations. In this thesis, I first examine an inventory management problem with unknown demand distribution and unknown substitution probability. The optimal inventory level depends upon both the demand distribution and substitution probability. Furthermore, the choice of inventory level influences the customer behavior we observe, and hence our learning about the demand distribution and substitution probability. I show that whether one should "stock more" or "stock less" so as to optimally acquire demand information depends critically on the perishability of inventory and observability of lost sales.; I then extend the study to an airline revenue management problem in which the manager dynamically controls inventory (seat capacity) to learn about customers' substitution behavior among multiple fare products. Estimating the customers' likelihood to substitute as well as their original purchase probability is crucial in determining the expected revenue-maximizing booking control policy. I show that the optimal Bayesian booking control policy for a two-fare model is a state-dependent base-stock policy. Simulation results further suggest that Bayesian booking control policy with observed substitution outperforms policies that do not account for active learning.; Finally, I study the forecast sharing problem in a two-level supply chain. Under a fairly general forecast evolution model, I quantify the magnitude of bullwhip effect reduction that results from forecast sharing. An effective way of sharing advance forecast information is to have the retailer place advance orders with the supplier. Placing advance orders generates advance demand information for the supplier and also eliminates the need for the supplier to guess the retailer's underlying ordering policy. I thus derive the optimal advance order quantity for the retailer, the quantity that optimally balances the need to respond to external demand changes and to reduce the bullwhip effect. In addition, I show that designing a proper transfer cost scheme between the supplier and the retailer improves the overall system performance.
机译:高效的信息获取和共享是在许多操作中释放潜在价值的关键。在本文中,我首先研究了具有未知需求分配和未知替代概率的库存管理问题。最佳库存水平取决于需求分配和替代概率。此外,库存水平的选择会影响我们观察到的客户行为,从而影响我们对需求分布和替代概率的了解。我表明,一个人应该“增加库存”还是“减少库存”以最佳地获取需求信息,关键取决于库存的易腐性和可观的销售损失。然后,我将研究扩展到航空公司收入管理问题,在该问题中,经理动态控制库存(座位容量)以了解客户在多种票价产品之间的替代行为。估计客户替代的可能性以及他们的原始购买可能性对于确定预期收益最大化的预订控制策略至关重要。我表明,针对两票价模式的最优贝叶斯预订控制策略是一种取决于国家的基础库存策略。仿真结果进一步表明,具有观察到的替代的贝叶斯预订控制策略的性能优于未考虑主动学习的策略。最后,我研究了两级供应链中的预测共享问题。在一个相当普通的预测演化模型下,我量化了由预测共享导致的牛鞭效应减少的幅度。共享预先预报信息的一种有效方法是让零售商与供应商下订单。发出预购订单可为供应商生成预需求信息,并且也无需供应商猜测零售商的基本订购政策。因此,我得出了零售商的最佳预购数量,该数量可以最佳地平衡对外部需求变化做出响应并减少牛鞭效应的需求。此外,我证明了在供应商和零售商之间设计适当的转移成本方案可以提高整体系统性能。

著录项

  • 作者

    Chen, Li.;

  • 作者单位

    Stanford University.;

  • 授予单位 Stanford University.;
  • 学科 Engineering Industrial.; Operations Research.
  • 学位 Ph.D.
  • 年度 2005
  • 页码 118 p.
  • 总页数 118
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 一般工业技术;运筹学;
  • 关键词

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