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

Hailin Sun, Che Lin Su, Xiaojun Chen

Research output: Journal article publicationJournal articleAcademic researchpeer-review

4 Citations (Scopus)

Abstract

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.
Original languageEnglish
Pages (from-to)361-389
Number of pages29
JournalMathematical Programming
Volume165
Issue number1
DOIs
Publication statusPublished - 1 Sep 2017

Keywords

  • Epi-convergence
  • Lower/upper semicontinuous
  • Multiproduct pricing
  • Regularized monotone linear complementarity problem
  • Sample average approximation
  • Stochastic linear complementarity problem

ASJC Scopus subject areas

  • Software
  • Mathematics(all)

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