Abstract

In this study, we research the problem of network revenue management with customer choice based on the Origin-Destination (O-D) demands. By dividing customers into different segments according to O-D pairs, we consider a network capacity control problem where each customer chooses the open product within the segment he belongs to. Starting with a Markov Decision Process (MDP) formulation, we approximate the value function with an affine function of the state vector. The affine function approximation results in a new Linear Program (LP) which yields tighter bounds than the Choice-based Deterministic Linear Program (CDLP). We give a column generation procedure for solving the LP within a desired optimality tolerance and present numerical results which show the policy perform from our solution approach can outperform that from the CDLP.

Keywords:

Choice behavior, dynamic programming, linear programming, network revenue management,

References

Competing interests

The authors have no competing interests.

Open Access Policy

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Copyright

The authors have no competing interests.