Markdown Optimization via Approximate Dynamic Programming


Cosgun O., KULA U., Kahraman C.

INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, vol.6, no.1, pp.64-78, 2013 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 6 Issue: 1
  • Publication Date: 2013
  • Doi Number: 10.1080/18756891.2013.754181
  • Title of Journal : INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS
  • Page Numbers: pp.64-78

Abstract

We consider the markdown optimization problem faced by the leading apparel retail chain. Because of substitution among products the markdown policy of one product affects the sales of other products. Therefore, markdown policies for product groups having a significant crossprice elasticity among each other should be jointly determined. Since the state space of the problem is very huge, we use Approximate Dynamic Programming. Finally, we provide insights on the behavior of how each product price affects the markdown policy.