In some developing countries, the port industry is going through rapid expansion, and regional port systems (RPSs) are gaining importance in their regional and national economies. In an idealized RPS, outbound freight generated within the region can be routed through any of the ports within the RPS. Commodity-handling capacities of ports within the RPS have a significant impact on the efficiency of commodity flow within the system. A bilevel optimization model that captures the interaction between the decisions of port capacity and commodity flow was developed in the context of a developing country with an export-oriented economy. In this model, a social planner optimizes the whole system by determining the capacity of each port to minimize certain regional logistics costs, taking into account that shippers in demand-generating hinterland regions determine the amount of shipments to each port on the basis of many factors, including the capacities of ports. A heuristic model was developed to solve the lower-level shipper-choice problem. This heuristic is not only based on discrete choice but also factored in port capacity constraints. The genetic algorithm was applied to solve the upper-level capacity-determination problem. The model was successfully applied to a port system containing 15 ports and 13 hinterland regions in Jiangsu province of China.
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