LAUSR

With the advancement of automation in transportation, the need to improve the operation efficiency of container terminals has increased. The most important determinant of container-handling efficiency is the productivity of equipment, such as quay cranes, automated lifting vehicles, storage yards, and yard cranes. Most previous studies have sought to optimize equipment assignments and scheduling independently and have considered only a loading or an unloading process. As loading and unloading processes occur simultaneously and the equipment operations are highly interrelated, it is important to direct the operations in an integrated manner that reflects the characteristics of automated container terminals. This paper presents a new mixed-integer programming model for analyzing the integrated problem of assigning resources and scheduling, which also considers the limited quantity of critical equipment. To solve the integrated optimization model, a genetic algorithm (GA) is developed. Since the critical equipment, such as yard cranes, are limited, and thus, restricting the efficiency of terminals, a sharing policy is proposed to improve the GA to shorten the operation time of both the loading and unloading processes. Experiments show that the improved GA proposed in this paper can obtain the optimal/near-optimal solutions in short CPU times, therefore it is efficient in solving the integrated equipment assignment and scheduling problem. The results obtained from the sharing policy are superior to those obtained from a non-sharing approach.