This paper studies joint decisions on pricing and empty container repositioning in two- depot shipping services with stochastic shipping demand. We formulate the problem as a stochastic dynamic programming (DP) model. The exact DP may have a high-dimensional state space due to in-transit containers. To cope with the curse of dimensionality, we develop an approximate model where the number of in-transit containers on each vessel is approxi- mated with a fixed container flow predetermined by solving a static version of the problem. Moreover, we show that the approximate value function is L♮-concave, thereby characterizing the structure of the optimal control policy for the approximate model. With the upper bound obtained by solving the information relaxation-based dual of the exact DP, we numerically show that the control policies generated from our approximate model are close to optimal when transit times span multiple periods.

Empty container repositioning, dynamic pricing, Markov decision process, L♮-concavity, approximate dynamic programming, duality
Transportation Science
Rotterdam School of Management (RSM), Erasmus University

Lu, T, Lee, C.Y, & Lee, L.H. (2019). Coordinating Pricing and Empty Container Repositioning in Two-Depot Shipping Systems. Transportation Science, Accepted. Retrieved from