Content area
Battery-powered automatic guided vehicles (B-AGVs) serve as crucial horizontal transportation equipment in terminals and significantly impact the terminal transportation efficiency. Imbalanced B-AGV availability during terminal peak and off-peak periods is driven by dynamic vessel arrivals. We propose a flexible dual-threshold charging (FDTC) strategy synchronized with vessel dynamics. Unlike the static threshold charging (STC) strategy, FDTC dynamically adjusts its charging thresholds based on terminal workload intensity. And we develop a collaborative B-AGV scheduling and routing optimization model incorporating FDTC. A tailored Dijkstra-Partition neighborhood search (Dijkstra-Pns) algorithm is designed to resolve the problem in alignment with practical scenarios. Compared to the STC strategy, FDTC strategy significantly reduces the maximum B-AGV running time and decreases conflict waiting delays and charging times by 25.04% and 24.41%, respectively. Moreover, FDTC slashes quay crane (QC) waiting time by 40.78%, substantially boosting overall terminal operational efficiency.
Details
Integer programming;
Cranes;
Collaboration;
Peak periods;
Optimization;
Decision making;
Charging;
Peripheral nervous system;
Literature reviews;
Algorithms;
Automation;
Transport buildings, stations and terminals;
Vessels;
Automated guided vehicles;
Strategic planning;
Workloads;
Energy consumption;
Efficiency;
Optimization models;
Run time (computers)
