Abstract
This paper presents a method for forecasting the yard inventory of container terminals over an extended period, and addresses an integrated yard planning problem for determining the optimal storage space utilization by considering the yard congestion effect on terminal performance. A formulation based on random variables and probabilistic functions was developed, which allows prediction of the storage space requirement without requiring fully-integrated simulation models. Then, an integrated cost objective function was defined. Numerical experiments were performed to illustrate how the forecasting model works and to support decision-making on yard planning and design for both inbound and outbound/transshipment areas.
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