LAUSR

This study proposes a job scheduling model and its heuristics for an automated container terminal with an overhead shuttle crane (OS) to reduce the total tardiness time of flatcars and external trucks by considering the separation of each job into a main job, and a premarshaling or remarshaling job. The OS is busy or idle according to the fluctuations in the processing times of different pieces of equipment. We identify the OS job sequencing problem considering job separation (OSJSPS) as a mixed-integer programming (MIP) model, which simultaneously sequences a set of jobs and searches for their possible separation into premarshaling and remarshaling jobs. We present a two-stage genetic algorithm (TGA) based on two local improvement procedures: an iterative local search procedure and an opportunistic job separation procedure. We conclude that the two-stage genetic algorithm reduces the total tardiness time of the container terminal’s flatcars and external trucks as the number of OS jobs increases.