Market-Driven Control in Container Terminal Management Larry Henesey , Fredrik Wernstedt, Paul Davidsson Blekinge Institute of Technology Ronneby/ Sweden, { lhe@bth.se , fwe@bth.se , pdv@bth.se } Abstract The steady, global increase in number of containers and the size of vessels able to carry containers is adding pressure to seaports and terminals to increase capacity. The alternative solution to increasing capacity other than physical expansion is via increased terminal performance so that containers are loaded, discharged, stored, and dispatched efficiently whilst optimizing available resources. The automatic planning of the operations of a container terminal via market-based allocation of resources may greatly benefit the container terminal in satisfying its objectives and meeting its goals. The proposal is that a Multi-Agent System approach would offer port or terminal managers a suitable tool to plan, coordinate, and manage the container terminal domain. There exists a variety of inputs and outputs, actors, intrinsic characteristics and a large number of combinations of factors influencing the output that makes it quite difficult to conduct analysis. In the suggested approach, the Multi-Agent System will plan and co-ordinate the processes within the terminal by mapping the objects and resources that are used in the terminal. The agents will be searching, coordinating, communicating, and negotiating with other agents via a market-based mechanism, a series of auctions, in order to complete their specified goal. 1. Introduction Seaports are important nodes in international shipping. The transfer of goods from one mode of transport to another model has been the primary function of seaports and more specifically, terminals. It is important to note that terminals are parts of a port where specialized cargoes are handled, e.g. passengers, autos, containers and oil. Ports are more than just piers. More than 90% of international cargo is moving between ports, Winklemans (2002). Of this increasingly growing trend, containerization has become the dominant method of moving unitized cargo in the world with many adverse effects such as the requirement for increasing space and causing congestion. This paper will pay particular attention to container seaports and container terminals. The needs for higher operational productivity, faster exchange of information, and speedier vessel turn-around times are just a few of many critical factors that are currently pressing port’s nodal position within logistics systems and supply chains. Logistics chains are stretching across continents where production may be in one continent and the market in another. Cargoes and shipments from all over the world have been increasing exponentially. However, seaports have not kept with the pace that economic development has been growing. In fact, many seaports are experiencing difficulties. There exist many bottlenecks in terms of information and physical status of the cargo leading to low productivity within the terminal. There are many obstacles in increasing terminal capacity through expansion, Notteboom and Winklemans (2002). In container terminals, the management of container terminal systems (CTS) is a decentralized, poorly structured, complex, and changeable problem domain, Gambardella et al. (1998), Rebello et al. (2000). It is important that the definition of terminal operation system be explained in that it is an operating system managing the flow of cargo through the terminal, ensuring that the cargo all go the right places and that the cargo movements are handled in the most efficient manner. Unfortunately, the few “off the shelf” programs that are available (i.e. NAVIS, based in Oakla nd, California and COSMOS NV. of Antwerp, Belgium) are designed for specific functions and not covering the total terminal operating system. The proposal to use Market Driven control implemented as a Multi-Agent System (MAS) in container management would provide control over the various sub systems found in a CT by decentralizing the problem solving tasks to the local area agents.