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SAA-regularized methods for multiproduct price optimization under the pure characteristics demand model

机译:纯特性需求模型下多制于多程序价格优化的SAA定期化方法

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摘要

Utility-based choice models are often used to determine a consumer's purchase decision among a list of available products; to provide an estimate of product demands; and, when data on purchase decisions or market shares are available, to infer consumers' preferences over observed product characteristics. These models also serve as a building block in modeling firms' pricing and assortment optimization problems. We consider a firm's multiproduct pricing problem, in which product demands are determined by a pure characteristics model. A sample average approximation (SAA) method is used to approximate the expected market share of products and the firm profit. We propose an SAA-regularized method for the multiproduct price optimization problem. We present convergence analysis and numerical examples to show the efficiency and the effectiveness of the proposed method.
机译:基于实用的选择模型通常用于确定可用产品列表中的消费者的购买决策; 提供对产品需求的估计; 而且,当可提供购买决策或市场份额的数据时,以推断消费者对观察到的产品特征的偏好。 这些型号还可以作为建模公司定价和分类优化问题的构建块。 我们考虑公司的多程序定价问题,其中产品需求由纯特征模型决定。 样本平均近似(SAA)方法用于近似产品的预期市场份额和公司利润。 我们提出了一种用于多元化价格优化问题的SAA定期化方法。 我们提供了收敛分析和数值例子,以显示提出的方法的效率和有效性。

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