Seaborne transportation contributes more than 80% by volume of the current cargos in the global trade. With the advent of large capacity vessels along with new locks of Panama Canal allowing passage of larger vessels, the US seaport warehouse faces double-sided challenge of accommodating the increasing demand within short time and low cost. Hence, in order to meet these challenges and store required volume of cargo in the warehouse, seaport warehouses need to improve their storage assignment operations.

This research work develops an integrated GIS-optimization framework to assign arriving cargos to a port warehouse lot. The model minimizes the total handling distance of cargo from dock to warehouse lots and from lots to the departure mode of transport. Firstly, the warehouse lots are divided into smaller storage units, known as cells, and the distance of each cell to the dock and to the different modes of transport are determined. A mixed integer linear programming model is developed to assign arriving cargos to cells and simultaneously rearrange the current cargo to efficiently utilize the available space. The optimization model is implemented on a lot in the Port of Beaumont, TX, to illustrate the effectiveness of the framework in reducing cargo handling time and cost. Implementing the framework decreases the total travelling distance for transporter trucks that drive inside the warehouses and decreases the waiting time the vessels spend at the anchorage area, respectively. The results obtained from the optimization model are visualized and updated in Google map for decision making purpose.