Perrot, A., Bourqui, R., Hanusse, N., Lalanne, F. and Auber, D. (2015) Large Interactive Visualization of Density Functions on Big Data Infrastructure. IEEE 5th Symposium on Large Data Analysis and Visualization, Chicago, 25-26 October 2015, 99-106.
https://doi.org/10.1109/LDAV.2015.7348077

has been cited by the following article:

• TITLE: An Agent-Based Approach to the Newsvendor Problem with Price-Dependent Demand

  AUTHORS: Patrick R. McMullen

  KEYWORDS: Optimization, Heuristic, Search

  JOURNAL NAME: American Journal of Operations Research, Vol.10 No.4, June 17, 2020

  ABSTRACT: This research presents an agent-based approach to finding near-optimal solutions to the newsvendor problem with price-dependent demand. The classical newsvendor problem is pursued where the decision of order quantity needs to be made in order to maximize expected profit. Here, the additional caveat of price-sensitive demand is included. This means that price (P) and order quantity (Q) are decision variables under the control of the newsvendor, with the intent of maximizing the expected value of the associated profit. The solution approach exploits an agent-based strategy, where an artificial agent traverses a grid-coordinate system of Price and Quantity values, where each unique Price and Quantity combination results in an expected profit. The agent-based approach consistently results in optimal solutions to a problem from the literature.