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Technical Note—Stochastic Optimization with Decisions Truncated by Positively Dependent Random Variables

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  • Xin Chen

    (Department of Industrial and Enterprise Systems Engineering, University of Illinois at Urbana–Champaign, Urbana, Illinois 61801)

  • Xiangyu Gao

    (Department of Decision Sciences and Managerial Economics, CUHK Business School, Chinese University of Hong Kong, Shatin, Hong Kong)

Abstract

We study stochastic optimization problems with decisions truncated by random variables. This paper extends existing results in the literature by allowing positively dependent random variables and a two-part fee structure. We develop a transformation technique to convert the original nonconvex problems to equivalent convex ones. We apply our transformation technique to an inventory substitution model with random supply capacities and a two-part fee cost structure. In addition, we extend our results to incorporate the decision maker’s risk attitude.

Suggested Citation

  • Xin Chen & Xiangyu Gao, 2019. "Technical Note—Stochastic Optimization with Decisions Truncated by Positively Dependent Random Variables," Operations Research, INFORMS, vol. 67(5), pages 1321-1327, September.
    • Handle: RePEc:inm:oropre:v:67:y:2019:i:5:p:1321-1327
    DOI: opre.2018.1815
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    References listed on IDEAS

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    Cited by:

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    2. Xin Chen & Menglong Li, 2021. "Discrete Convex Analysis and Its Applications in Operations: A Survey," Production and Operations Management, Production and Operations Management Society, vol. 30(6), pages 1904-1926, June.

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