The paper aims to tackle the automated guided vehicles (AGVs) scheduling problem at container terminals, considering buffer location constraints and job-to-QC sequences to optimize outbound container handling, while minimizing makespan and penalty time.
Two mixed integer programming models are developed to address the scheduling issue, incorporating practical constraints like time windows and QC blockings. The paper also presents lemmas, propositions and various algorithms (sequential insertion, random search, greedy insertion and improved genetic algorithm (GA)) for feasible scheduling.
The study finds that the proposed algorithms are competitive against commercial solvers, providing effective solutions for AGV and QC scheduling, thus enhancing the efficiency of QC operations.
The paper’s originality lies in modeling AGV queueing activities, the rescheduling process for container transport and integrated scheduling optimization of QC and AGV. It offers managerial insights through numerical experiments, showcasing the algorithms’ effectiveness.
