A Local Search-Based Heuristic for Optimizing AGV Routing in Automated Port Environment

Overview & Synopsis

The use of Automated Guided Vehicles for container loading and unloading has emerged as a key solution in response to the increasing demand for port efficiency, driven by the growing volume of port operations. We formulate a routing problem, extended from existing literature, that determines the trajectories of these vehicles in an automated port environment while ensuring collision-free paths. We show that when the physical paths of the AGVs is fixed the problem reduces to a job shop scheduling problem with blocking constraints and no swap allowed, very little studied in the literature. We also develop an Iterative Path Reinsertion algorithm to improve the trajectories of the AGV for a given solution. Results show the efficiency of our approach both in terms of solution quality and of computational time for instances of various sizes. The conclusion outlines future research directions.