Strategies for dynamic appointment making by container terminals

We consider a container terminal that has to make appointments with barges dynamically, in real-time, and partly automatic. The challenge for the terminal is to make appointments with only limited knowledge about future arriving barges, and in the view of uncertainty and disturbances, such as uncertain arrival and handling times, as well as cancellations and no-shows. We illustrate this problem using an innovative implementation project which is currently running in the Port of Rotterdam. This project aims to align barge rotations and terminal quay schedules by means of a multi-agent system. In this\ud paper, we take the perspective of a single terminal that will participate in this planning system, and focus on the decision making capabilities of its intelligent agent. We focus on the question how the terminal operator can optimize, on an operational level, the utilization of its quay resources, while making reliable appointments with barges, i.e., with a guaranteed departure time. We explore two approaches: (i) an analytical approach based on the value of having certain intervals within the schedule and (ii) an approach based on sources of exibility that are naturally available to the terminal. We use simulation to get insight in the benefits of these approaches. We conclude that a major increase in utilization degree could be achieved only by deploying the sources of exibility, without harming the waiting time of barges too much

Aligning barge and terminal operations using service-time profiles.

We consider a key issue in hinterland container navigation in ports, such as Rotterdam and Antwerp, namely the barge handling problem: how to optimize the alignment of barge and terminal operations in a port. We make a major step in solving the barge handling problem for practical settings. Specifically, we consider restricted opening times of terminals, unbalanced networks, the presence of sea vessels, and closing times of containers. Consequently, at a terminal a barge faces time dependency in: (1) the waiting time until the start of handling and (2) the handling time itself. The concept of waiting profiles which we introduced in an earlier paper only deals with (1). To deal with (1) and (2) together we introduce a more comprehensive concept, namely that of service-time profile. To establish how well our approach works, we evaluate the performance of our distributed planning approach extensively by means of simulation. We compare our results with those based on centralized planning by using an off-line benchmark resembling it. We show that the Multi-Agent system that we introduce enables barge and terminal operators to align their operations efficiently. Hence, it can be seen as a promising solution approach for solving the barge handling problem, since it enables (competing) companies to collaborate in a competitive way