This thesis carries out the capacity expansion strategy for port in a competition environment. A new model which deals sea port as a node in the logistic chain will be built in this study. And the port of Rotterdam and port of Antwerp will be used as a special case study. Nowadays containers are widely used in world trade business. Millions of containers are being moved from one point to another every single day. In the last decades, world container traffic has increased enormously because of the increasing wodd population and the more specific needs of customers. The world container traffic increased from around 100 Million TEU in 1990 to around 400 Million TEU in 2005 (Hofstra University). And the container traffic is expected to remain growing in the future. The growth in international container shipping will continue with the expected percentage of 9% annually up to 2015 (Heymann, 2006). Ports, as facilities for accommodate ships and transferring cargoes, play essential nodes in maritime-land freight transport network. The strong growth in container industry, gives a good opportunity for port development on one hand. On the other hand, ports are facing great pressure of handling with the rapid-growing container traffic. Due to the enormous growth in total demand and uncertain demand fluctuation in short periods, ports are always faced with capacity problems, either short-capacity or over-capacity. When taking into account new trends in containerization, and intensively increasing competition among ports in regional port clusters, port planning in capacity will become even more significant. Therefore, developing best strategies to deal with port capacity expansion problems in competitive environments is a main challenge faced by port authonties. In order to provide information to port authorities when they make port capacity expansion strategies, simulation models are widely used. In these simulation models, main focus is on hinterland transport network, because of the quality of hintedand transport has become increasingly important for the competitiveness of a seaport (Konings, 2007). Basically, two types of approaches for transport modeling can be used in transportation planning concerning port capacity problems. One is simulation of route assignment in network, e.g. the SMILE model (Strategic Model for Integrated Logistics and Evaluation) developed by the Dutch institute TNO, which simulates the assignment of freight flows for different commodity types and transportation modes. The other one is projection of port demand based on macro-economic relationships with a more or less fixed market share for a particular port. The example of this second approach is the GSM model (Goederen Stromen Model) used by the Port of Rotterdam. But there are some limitations in these two approaches. The first approach does not account for port development. This approach mainly focuses on hinterland transportation network. However, port investment characteristics are not taken into account in this approach. The second approach accounts for port development, but does not incorporate the potential changes in a port's market share caused by, for instance, competition between transportation routes or port service level. In this case, it is essential to develop a new model, which combine these two fore-mentioned approaches, with the capability of both simulating the effect of competition and incorporating autonomous demand growth. In this thesis, a new concept is formulated that sea port is considered as a node in total logistic chain. A new dynamic port planning model is developed with Microsoft Excel Program. In this port planning model, factors of port capacity, port-commercial and public interests, port competition, capacity problems of hinterland infrastructures are all taken into consideration. An actor analysis is firstly carried out in the thesis. The main actors in container industry are analyzed, including terminal operators, port authorities, shipping companies, inland transport operators, manufacturers and consignees. Market share, port utilization, traffic volume, and unit cost are concluded as the main interests of port authorities. Based on the conclusions of actor analysis, the port planning model is developed with three key inputs, including (1) port residence cost and congestion; (2) port investment cost; (3) hintedand transport cost and congestion. This model is developed based on the following iterative mechanism: In one year, these three aspects (i.e. port residence cost, port investment cost, and hintedand transport cost) determine the unit transshipment cost per TEU of this same year and ultimately determine ports' market share of the same year. However, the market share of this year would determine the three costs of the next following year (i.e. port residence cost, port investment cost, and hintedand transport cost). In the iterative process, several other factors are also included. Port capacity also affects the port residence cost of the same year. The new capacity added is another factor that affects the port investment costs of the same year. Hintedand infrastructure also affects the hintedand transport cost of the same year. A case study is earned out by means of the port-planning model. In this case study, port of Antwerp and port of Rotterdam are chosen as the two competition ports. Time honzon of 30 years is analyzed with thirty iterations. First of all, a general descnption of both ports is shown, including geographical location, histoncal overview, port statistics, hintedand connection, future expansion planning and containenzation in each port. Based on this basic port information, five scenarios and assumptions are made as follows: changing expansion plans; changes in port congestion; changes in hintedand congestion; global economy development; combination of strategies with uncertainty. The first two scenarios (changing expansion plans and changes in port congestion) can be fully determined by port authorities.