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Network revenue management with inventory-sensitive bid prices and customer choice

Research output: Contribution to journalJournal article

Published
<mark>Journal publication date</mark>16/01/2012
<mark>Journal</mark>European Journal of Operational Research
Issue number2
Volume216
Number of pages10
Pages (from-to)459-468
Publication StatusPublished
<mark>Original language</mark>English

Abstract

We develop an approximate dynamic programming approach to network revenue management models with customer choice that approximates the value function of the Markov decision process with a non-linear function which is separable across resource inventory levels. This approximation can exhibit significantly improved accuracy compared to currently available methods. It further allows for arbitrary aggregation of inventory units and thereby reduction of computational workload, yields upper bounds on the optimal expected revenue that are provably at least as tight as those obtained from previous approaches. Computational experiments for the multinomial logit choice model with distinct consideration sets show that policies derived from our approach can outperform some recently proposed alternatives, and we demonstrate how aggregation can be used to balance solution quality and runtime.