Non-cooperative competition among revenue maximizing service providers with demand learning

Changhyun Kwon, Terry Lee Friesz, Reetabrata Mookherjee, Tao Yao, Baichun Feng

Research output: Contribution to journalArticle

21 Scopus citations

Abstract

This paper recognizes that in many decision environments in which revenue optimization is attempted, an actual demand curve and its parameters are generally unobservable. Herein, we describe the dynamics of demand as a continuous time differential equation based on an evolutionary game theory perspective. We then observe realized sales data to obtain estimates of parameters that govern the evolution of demand; these are refined on a discrete time scale. The resulting model takes the form of a differential variational inequality. We present an algorithm based on a gap function for the differential variational inequality and report its numerical performance for an example revenue optimization problem.

Original languageEnglish (US)
Pages (from-to)981-996
Number of pages16
JournalEuropean Journal of Operational Research
Volume197
Issue number3
DOIs
StatePublished - Sep 16 2009

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

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