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

Math. Program.(2017)

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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.
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关键词
Stochastic linear complementarity problem,Epi-convergence,Lower/upper semicontinuous,Sample average approximation,Regularized monotone linear complementarity problem,Multiproduct pricing,90B50,90C15,90C26
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