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Technical note - Stochastic optimization with decisions truncated by positively dependent random variables

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)1321-1327
Number of pages7
JournalOperations Research
Volume67
Issue number5
DOIs
StatePublished - 2019

Keywords

  • Dependent supply capacity uncertainty
  • Inventory management
  • Risk aversion
  • Stochastic optimization
  • Two-part fee structure

ASJC Scopus subject areas

  • Computer Science Applications
  • Management Science and Operations Research

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