An Analysis on the Modeling of Container Terminal Operations

Objectives: Container terminals are essential intermodal interfaces in the global transportation network. Efficient container handling at terminals is important in reducing transportation costs and keeping shipping schedules. The present analysis describes these problems within the scope of container terminal modeling. Methods/Statistical Analysis: Basic formulation of the problem is stated as two-machine flow shop problem. The well-known maximum travelling salesman problem (Max TSP) has been applied in this study. Max TSP can be solved as a TSP by replacing each edge cost by its additive inverse, since, there is a different value for unloading stack i while loading stack j and loading stack i while unloading stack j; this model corresponds to the Asymmetric Travelling Salesman Problem (ATSP). Findings: It is found that, there is an essential need for improvements and optimization of all aspects in the container transportation chains. For the real life systems of this type, this problem has been solved optimally. Significant possibilities for time savings have been arrived in this study. For real life case, where the reloading is performed on two barges placed side by side (8 stacks in the bay, 11 bays, 4 containers in the stack) time savings as a function of the terminal length are presented. The time saving with respect to number of rows inside the container yard is presented. Simulation models of container cranes demonstrate significant time savings, if double cycling is applied. It is showed that application of the double cycling can result in time savings of 12 to 27 % depending on the system parameters. This analysis is based on discrete event simulation and analytical optimization methods. Application/Improvement: Good planning of container terminal operations reduces waiting time for liner ships. Reducing the waiting time increases customer satisfaction and improves the terminal productivity which gives the container terminal an advantage over its competitors.