Decision making in decentralized shipping network with stochastic revenue based empty container repositioning

Shipping companies costs related to handling and moving empty containers (due to trade imbalance between different parts of the world) have become a significant part of the total operational costs bared by the companies, with consequent pressure on the profit level. This is the empty container repositioning problem (ECR): at each port of call, we need to choose how many empty containers to reposition, thus losing the ability to accept demand, and the resulting potential profit. This work solves the ECR considering: 1) inelastic demand faced by shipping companies; 2) freight rate uncertainty; and 3) differing objectives between the equipment office who oversees repositioning containers and the local offices selling the vessel space. We propose a Target Price Policy where the equipment office could charge local sales offices the target prices derived from a stochastic model to push them to make better demand fulfillment decisions. The proposed Target Price policy does not require accurate forecast of future price and demand, hence showing its practical value. The optimal target prices are also influenced by the price distribution: the volatility of price has a larger impact on the desired level of imbalance between eastbound laden container flow and westbound laden container flow.