Battery-Powered AGV Scheduling and Routing Optimization with Flexible Dual-Threshold Charging Strategy in Automated Container Terminals
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| Xuất bản năm: | Journal of Marine Science and Engineering vol. 13, no. 8 (2025), p. 1526-1553 |
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| Tác giả chính: | |
| Tác giả khác: | , , , |
| Được phát hành: |
MDPI AG
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| Những chủ đề: | |
| Truy cập trực tuyến: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 001 | 3244043370 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2077-1312 | ||
| 024 | 7 | |a 10.3390/jmse13081526 |2 doi | |
| 035 | |a 3244043370 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231479 |2 nlm | ||
| 100 | 1 | |a Guo Wenwen | |
| 245 | 1 | |a Battery-Powered AGV Scheduling and Routing Optimization with Flexible Dual-Threshold Charging Strategy in Automated Container Terminals | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a 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. | |
| 653 | |a Scheduling | ||
| 653 | |a Integer programming | ||
| 653 | |a Cranes | ||
| 653 | |a Collaboration | ||
| 653 | |a Peak periods | ||
| 653 | |a Optimization | ||
| 653 | |a Decision making | ||
| 653 | |a Charging | ||
| 653 | |a Peripheral nervous system | ||
| 653 | |a Literature reviews | ||
| 653 | |a Algorithms | ||
| 653 | |a Automation | ||
| 653 | |a Transport buildings, stations and terminals | ||
| 653 | |a Vessels | ||
| 653 | |a Automated guided vehicles | ||
| 653 | |a Strategic planning | ||
| 653 | |a Workloads | ||
| 653 | |a Energy consumption | ||
| 653 | |a Efficiency | ||
| 653 | |a Optimization models | ||
| 653 | |a Run time (computers) | ||
| 653 | |a Economic | ||
| 700 | 1 | |a Hu Huapeng | |
| 700 | 1 | |a Sha Mei | |
| 700 | 1 | |a Lian Jiarong | |
| 700 | 1 | |a Yang Xiongfei | |
| 773 | 0 | |t Journal of Marine Science and Engineering |g vol. 13, no. 8 (2025), p. 1526-1553 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3244043370/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3244043370/fulltextwithgraphics/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3244043370/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |