An intelligent decision support system prototype for hinterland port logistics

Port logistics is characterised by a high degree of fragmentation, uncertainty and complexity. In a context with these characteristics, decision support can be of significant value. This study presents the prototype of an intelligent decision support system (DSS) that leads to horizontal and vertical cooperation among freight agents involved in port logistics. A multi-agent simulation model is presented where heterogeneous actions are enabled as a result of an adaptive reinforcement learning algorithm that is inspired by human decision-making strategies. The model combines optimisation modelling and decision theory to operate in a dynamic environment characterised by information asymmetry among agents and dynamic changes over time. A simulation demonstrates the dynamics and convergence to equilibrium of the interactions of heterogeneous agents for delivery and pick up of import/export shipments. In particular, we answer two specific research questions. What is the likely impact of an intelligent DSS in hinterland container transport as a value-added service of port community system (PCS)? How can an optimum cooperative strategy be formulated to meet the dynamic demand and supply of freight agents in hinterland container transport and achieve agility in the age of hyper-competition? By addressing these two research questions we make a specific contribution by developing an agent-based simulation model in a real-world and large-scale case study, by using a reinforcement learning model based on probability matching theory that allows simulating realistically the adaptive behaviour of agents. The results of the simulation of two weeks of container movements indicate huge savings in total transport costs and distance travelled as well as higher utilisation of trucks from the sharing of resources. Moreover, we show that it is strictly better for smaller freight agents to cooperate a conclusion generated endogenously inside the model as a tradeoff between exploration and exploitation. As a result of this prototype simulation, major freight agents will not necessarily benefit from the DSS mainly because they are already using the economies of scale.