With the increasing volume of container freight transport, future port planning is crucial. Simulation models provide a means to gain insight in the effects of terminal expansions. Detailed simulations incorporate berth allocation: assigning vessels a time and location at the quay wall, where the vessel is loaded and unloaded. This article develops decision models for both offline preliminary berth planning and for online recovery of this plan during simulation. First, we develop an optimisation-based approach that incorporates realistic aspects—cyclic vessel arrivals, tidal windows, and minimisation of vessel draught during low water periods—in order to develop a cyclic baseline berth allocation plan. The approach can proactively incorporate slack for increased robustness. Exploiting a constraint-based solver, we can obtain optimal or satisficing solutions for a year’s operation of a large port. The resulting preliminary berth plan is used as a basis for the arrival times. However, disruptions can occur, such as vessel arrival and loading times varying from the planned. Hence, second, we develop a real-time disruption management decision model. This multi-level heuristic approach reacts to disruptions while minimising perturbation of the original berth plan. Computational experiments with a high-resolution simulator show our recovery approach finds good solutions until a tipping point of disturbance. Results also show that when the expected occupation of a terminal is higher, strengthening robustness of the preliminary plan has increased importance. The approach described in the article is implemented for a major European inland tidal port, forming the basis of a simulation-based decision support tool for operational planning and exploring port expansion options.

The perception of warmth and competence in others influences social interaction and decision making. Virtual agents have been used in many domains including serious gaming and training. In this work we study the effect of warmth expressed in the behavior of a virtual agent on a human-agent negotiation. We design and conduct an experiment where participants negotiate with two versions of the same agent displaying varying levels of warmth. The results show that humans are more satisfied with the warm agent, are more willing to renegotiate with it, would recommend the agent more to their friends and had a better interaction experience, even though there is no difference in negotiation outcome (utility, agreement or rounds needed). While studies have shown effects of emotional displays on negotiation and collaboration, this is - to our knowledge - the first time that a clear effect of behavioral style is shown on the post-hoc appraisal of a human-agent collaboration, in our case a negotiation.