基于约束编程的地下煤矿中的电动轮胎车辆的时间表优化
Maoquan Wan1,2, Hao Li1,2, Hao Wang2,3
1Research Institute of Mine Software, Chinese Institute of Coal Science, Beijing 100013, China.
Sensors (Basel, Switzerland)
|September 19, 2025
概括
这项研究优化了使用新型约束编程框架在地下矿山中的电动轮胎车 (ERTV) 调度. 这种方法显著减少了里程,充电需求和车辆使用量,同时提高了效率.
科学领域:
- 运营研究 运营研究
- 采矿工程 采矿工程 采矿工程
- 机器人和自动化机器人与自动化
背景情况:
- 地下煤矿面临复杂的ERTV调度挑战,原因是狭窄的空间和动态需求.
- 整合清洁能源需要有效的资源管理和可持续的物流.
研究的目的:
- 开发一个优化框架,用于ERTV计划在地下矿山.
- 解决时空充电冲突,提高计算效率.
主要方法:
- 一个基于约束编程 (CP) 的优化框架,集成虚拟充电站映射 (VCSM).
- 一个新的RFID视觉融合定位系统,可提供可靠的时空数据.
- 一个动态拓调整算法,以提高计算效率.
主要成果:
- 实现了总运输里程减少17.6%.
- 充电事件减少了60%,车辆使用量减少了33%.
- 与MILP相比,计算效率提高了54.4%,消除了时间窗口违规.
结论:
- 拟议的框架提供了一个强大而可扩展的解决方案,用于在封闭的地下环境中可持续的ERTV调度.
- 该方法平衡了经济和运营目标,适用于工业物流和清洁采矿.
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