Dynamic resource allocation for intermodal freight transportation with network effects: Approximations and algorithms

- Formulate a MDP model with discrete product demands for the dynamic resource allocation problem in intermodal transportation.
- Generalize the one-customer-an-interval assumption which persists in traditional booking control models.
- Find an equivalent STOC model formulation of the MDP model under arbitrary discrete demands.
- Build a rich class of deterministic and stochastic approximation models of the MDP model.
- Propose a number of easy-to-implement intermodal resource allocation policies.

This paper investigates a dynamic resource allocation problem, in which an intermodal operator attempts to determine the policy that characterizes the optimal quantities of each service product allowed to be sold during each time interval within a finite selling horizon. The problem is formulated as a Markov decision process (MDP) model and a variety of mathematical programming models are developed to approximate the MDP model. A series of policies are obtained from the optimal solutions to the approximation models and theoretical results are provided to characterize the comparisons between the MDP model and the approximation models. Various policies are further evaluated through theoretical analysis and simulation tests. We finally gain insights into the importance of the dynamic decisions, stochastic demands, model re-solving, and integer variables in formulating approximation models.