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Cluster :  Tutorials

Session Information  : Sunday Nov 05, 10:00 - 11:30

Title:  Tutorial: Math Programming Approaches to Approximate Dynamic Programming

Abstract Details

Title: Math Programming Approaches to Approximate Dynamic Programming
 Presenting Author: Dan Adelman,Professor of Operations Management, University of Chicago, Graduate School of Business, 5807 South Woodlawn Avenue, Chicago IL 60637, United States, dan.adelman@gsb.uchicago.edu
 
Abstract: Approximate Dynamic Programming (ADP) is a new class of methods for breaking Bellman's curse of dimensionality. We summarize math programming approaches to ADP, focusing on applications in inventory control, revenue management and queueing. We derive a parsimonious, exactly solvable math program whose optimal dual prices are used to construct a value function approximation. Dual information provides economic insights, including a "price-directed" control policy.