Abstract
This paper addresses the joint vehicle dispatching and storage allocation problem in automated container terminals (ACTs). Two types of popular vehicles used in ACTs are considered in this problem: automated lifting vehicles (ALVs) and automated guided vehicles (AGVs). Two mixed-integer linear programming (MILP) models are proposed for the two types of vehicles, with the goal of minimizing the vehicle operating costs. To solve these models, this study develops a three-stage decomposition approach called particle swarm optimization, based on greedy search. Numerical experiments verify the applicability of the proposed models and the efficiency of the proposed algorithm. The study provides an effective vehicle management tool for terminal managers to handle vehicle dispatches in daily operations.
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