An approximate dynamic programming approach to network revenue management with customer choice

An approximate dynamic programming approach to network revenue management with customer choice

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Article ID: iaor200970703
Country: United States
Volume: 43
Issue: 3
Start Page Number: 381
End Page Number: 394
Publication Date: Aug 2009
Journal: Transportation Science
Authors: ,
Keywords: programming: dynamic, yield management
Abstract:

We consider a network revenue management problem where customers choose among open fare products according to some prespecified choice model. Starting with a Markov decision process (MDP) formulation, we approximate the value function with an affine function of the state vector. We show that the resulting problem provides a tighter bound for the MDP value than the choice-based linear program. We develop a column generation algorithm to solve the problem for a multinomial logit choice model with disjoint consideration sets (MNLD). We also derive a bound as a by-product of a decomposition heuristic. Our numerical study shows the policies from our solution approach can significantly outperform heuristics from the choice-based linear program.

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