A genetic algorithm for the storage location of containers at a seaport terminal

Abstract

This research focuses on an improved use of the storage area by reducing the time for the yard cranes to transfer containers from the storage area to the marshalling area for loading onto the vessels. Minimizing the handling time of containers in the storage yard reduces to the problem of finding an efficient stacking strategy and a loading schedule that avoids unnecessary moves of containers in the storage yard. Two loading strategies are examined, namely LCFS and FCFS in terms of handling time in the storage area. Results show that an LCFS loading schedule is far more efficient than an FCFS schedule. A genetic algorithm (GA) is used to optimize both loading schemes. The effect of the genetic operators on the solutions are analyzed and results show that a GA with mutation as operator only is best in finding efficient solutions.