井工煤矿无轨胶轮车全局调度模型

陈湘源; 潘涛; 周彬

doi:10.13272/j.issn.1671-251x.2023010006

井工煤矿无轨胶轮车全局调度模型

doi: 10.13272/j.issn.1671-251x.2023010006

1.
国能榆林能源有限责任公司，陕西榆林　719000
2.
国能信息技术有限公司，北京　100011
3.
北京航空航天大学车路一体智能交通全国重点实验室，北京　100191

基金项目: 国家自然科学基金项目（52102448）；国家重点研发计划项目（2022YFB4703702）。

详细信息

作者简介:
陈湘源（1972—），男，内蒙古鄂尔多斯人，高级工程师，硕士，主要研究方向为智能化与机电系统安全，E-mail：shyscxy@163.com。通信作者：潘涛(1975—)，男，江苏连云港人，教授级高级工程师，博士，现主要从事矿山智能化、信息化方面的研究工作，E-mail：pancumt@163.com

中图分类号: TD54
计量
- 文章访问数: 104
- HTML全文浏览量: 33
- PDF下载量: 16
- 被引次数: 0
出版历程
- 收稿日期: 2023-01-03
- 修回日期: 2023-12-10
- 网络出版日期: 2024-01-04

Global scheduling model for trackless rubber-tyred vehicle in underground coal mines

1.
CHN Energy Yulin Energy Co., Ltd., Yulin 719000, China
2.
CHN Energy Information Technology Co., Ltd., Beijing 100011, China
3.
State Key Lab of Intelligent Transportation System, Beihang University，Beijing 100191, China

摘要

摘要:
井工煤矿无轨胶轮车数量多，运输易受搬家倒面、突发事件等影响，传统的人工调度方法效率低，且易造成车辆闲置、空载、里程浪费等问题，而现有的辅助运输车辆调度方法大多面向固定任务使用离散事件优化的方案，将全局模型拆解为局部模型，缺乏对井工煤矿整体情况的分析。针对上述问题，提出了一种基于百度工业求解器的井工煤矿无轨胶轮车全局调度模型，介绍了该模型中信息收集模块、数据建模模块和工业求解器模块设计方案，以及无轨胶轮车全局调度流程。该模型采用基于“分批求解、迭代优化”的无轨胶轮车全局调度算法，由百度工业求解器基于动作调整启发式算法对车辆调度问题进行优化求解，解决了传统调度模型求解时间长、易陷入局部最优解等问题。实验结果表明，基于百度工业求解器的井工煤矿无轨胶轮车全局调度模型较人工调度方法大幅降低了使用车次，提高了车辆运转效率，调度优化的求解时间低于基于Gurobi求解器的局部调度模型，更适用于井下辅助运输场景下大规模复杂调度任务。
- 井工煤矿 /
- 辅助运输 /
- 无轨胶轮车 /
- 车辆调度 /
- 全局调度优化 /
- 百度工业求解器
Abstract:
There are a large number of trackless rubber-tyred vehicles in underground coal mines. The transportation is easily affected by moving surfaces, emergencies, and other factors. Traditional manual scheduling methods are inefficient and prone to problems such as idle, empty, and wasted vehicles. However, existing auxiliary transportation vehicle scheduling methods mostly focus on fixed tasks using discrete event optimization schemes. It breaks down the global model into local models, and lacks analysis of the overall situation of underground coal mines. In order to solve the above problems, a global scheduling model for trackless rubber-tyred vehicle in underground coal mines based on Baidu industrial solver is proposed. The design scheme of the information collection module, data modeling module, and industrial solver module in this model are introduced, as well as the global scheduling process for trackless rubber-tyred vehicles. This model adopts a global scheduling algorithm for trackless rubber-tyred vehicles based on "batch solving and iterative optimization". The vehicle scheduling problem is optimized and solved by Baidu industrial solver based on action adjust heuristic algorithm. It solves the problems of long solving time and easy getting stuck in local optimal solutions in traditional scheduling models. The experimental results show that the global scheduling model for trackless rubber-tyred vehicles based on Baidu industrial solver significantly reduces the number of vehicles used and improves vehicle operation efficiency compared to manual scheduling methods. The solution time for scheduling optimization is lower than that of the local scheduling model based on Gurobi solver. It is more suitable for large-scale complex scheduling tasks in underground auxiliary transportation scenarios.
- underground coal mine /
- auxiliary transportation /
- trackless rubber-tyred vehicles /
- vehicle scheduling /
- global scheduling optimization /
- Baidu industrial solver

HTML全文

图 1 无轨胶轮车全局调度模型运行流程

Figure 1. Operation process of global scheduling model for trackless rubber-tyred vehicle

下载: 全尺寸图片幻灯片

图 2 百度工业求解器优化算法流程

Figure 2. Optimization algorithm process of Baidu industrial solver

下载: 全尺寸图片幻灯片

表 1 地图信息采集器功能

Table 1. Function of map information collector

功能名称	功能描述
巷道采集	采集竖井和巷道坐标，进行巷道和坐标相关操作（包括新增巷道、修改巷道、删除巷道、停用巷道、新增坐标记录、修改坐标记录、删除坐标记录、停用坐标记录），重绘巷道，绘制指定时刻的巷道状态
点对象采集	选择点对象类型树，图选点对象，进行点对象和坐标相关操作（新增对象、删除对象、修改对象、停用对象、新增坐标记录、删除坐标记录、修改坐标记录、停用坐标记录）
线对象采集	选择线对象类型树，图选线对象，进行线对象和坐标相关操作（新增线对象、删除线对象、修改线对象、停用线对象、新增坐标记录、删除坐标记录、修改坐标记录、停用坐标记录）

下载: 导出CSV

表 2 第1组和第2组无轨胶轮车调度问题的求解结果

Table 2. Calculated results for group 1 and group 2 scheduling problems of trackless rubber-tyred vehicle

组别	调度方法	使用车次	完成工单个数	运输物料个数
第1组	人工调度	15	10	13
	基于Gurobi求解器	14	11	16
	基于百度工业求解器	11	11	16
第2组	人工调度	21	8	20
	基于Gurobi求解器	14	10	21
	基于百度工业求解器	14	10	21

下载: 导出CSV

表 3 第3—5组无轨胶轮车调度问题的求解结果

Table 3. Calculated results for group 3, group 4 and group 5 scheduling problems of trackless rubber-tyred vehicle

组别	调度方法	使用车次	完成工单个数	运输物料个数
第3组	人工调度	26	10	20
	基于Gurobi求解器	17	12	21
	基于百度工业求解器	14	13	21
第4组	人工调度	154	44	153
	基于Gurobi求解器	21	46	197
	基于百度工业求解器	20	46	197
第5组	人工调度	228	58	225
	基于Gurobi求解器	36	56	274
	基于百度工业求解器	36	59	280

下载: 导出CSV

表 4 2种无轨胶轮车调度模型的求解时间

Table 4. Calculated time of two scheduling models for trackless rubber-tyred vehicle

可用车辆数/辆	工单个数	运输物料个数	求解时间/s
可用车辆数/辆	工单个数	运输物料个数	基于Gurobi 求解器	基于百度工业求解器
56	3	3	5.23	4.78
	10	10	10.01	8.99
	14	16	23.47	21.29
	14	25	29.62	27.25
106	3	3	17.69	16.19
	10	10	21.07	19.35
	14	16	33.57	30.15
	14	25	50.52	46.63
	46	198	442.39	399.48
	60	284	504.72	453.71

下载: 导出CSV

表 5 不同批尺度下的无轨胶轮车调度优化结果

Table 5. Scheduling optimization results of trackless rubber-tyred vehicle under different batch-size

组别	批尺度	使用车次	完成工单个数	运输物料个数	求解时间/s
第4组	15	22	44	194	243.92
	25	20	46	197	399.48
	40	19	46	197	2622
第5组	15	40	55	269	284.37
	25	36	59	280	453.71
	40	36	59	281	3441

下载: 导出CSV

参考文献(21)

[1]	秦高威,李红旗,王洪恩. 赵固矿区辅助运输系统提效研究[J]. 煤矿机械,2018,39(9):39-40. QIN Gaowei,LI Hongqi,WANG Hong'en. Research on efficiency of auxiliary transportation system in Zhaogu Coal Mine Area[J]. Coal Mine Machinery,2018,39(9):39-40.
[2]	糜瑞杰,杨双锁,杨欢欢,等. 副井无轨胶轮车辅助运输系统的应用研究[J]. 矿业研究与开发,2019,39(6):114-117. MI Ruijie,YANG Shuangsuo,YANG Huanhuan,et al. Application research on auxiliary transportation system of trackless rubber wheel vehicle in auxiliary shaft[J]. Mining Research and Development,2019,39(6):114-117.
[3]	杨坤. 矿井无轨胶轮车智能化管理系统研究[J]. 工矿自动化,2023,49(1):162-170. YANG Kun. Research on the intelligent management system of the trackless rubber-tyred vehicles in the coal mine[J]. Journal of Mine Automation,2023,49(1):162-170.
[4]	袁晓明. 煤矿无轨辅助运输工艺和发展方向研究[J]. 煤炭工程,2019,51(5):1-5. YUAN Xiaoming. Analysis of coal mine trackless auxiliary transportation technology and the development direction[J]. Coal Engineering,2019,51(5):1-5.
[5]	陈晓晶. 井工煤矿运输系统智能化技术现状及发展趋势[J]. 工矿自动化,2022,48(6):6-14,35. CHEN Xiaojing. Current status and development trend of intelligent technology of underground coal mine transportation system[J]. Journal of Mine Automation,2022,48(6):6-14,35.
[6]	王国法, 杜毅博. 煤矿智能化标准体系框架与建设思路[J]. 煤炭科学技术,2020,48(1):1-9. WANG Guofa, DU Yibo. Coal mine intelligent standard system framework and construction ideas[J]. Coal Science and Technology,2020,48(1):1-9.
[7]	王国法,杜毅博. 智慧煤矿与智能化开采技术的发展方向[J]. 煤炭科学技术,2019,47(1):1-10. WANG Guofa,DU Yibo. Development direction of intelligent coal mine and intelligent mining technology[J]. Coal Science and Technology,2019,47(1):1-10.
[8]	孙继平,江嬴. 矿井车辆无人驾驶关键技术研究[J]. 工矿自动化,2022,48(5):1-5,31. SUN Jiping,JIANG Ying. Research on key technologies of mine unmanned vehicle[J]. Journal of Mine Automation,2022,48(5):1-5,31.
[9]	鲍新平,汪涛. 基于AI视觉智能识别的煤矿斜井轨道运输安全管理系统[J]. 工矿自动化,2023,49(增刊1):72-75. BAO Xinping,WANG Tao. A safety management system for coal mine inclined shaft rail transportation based on intelligent AI visual recognition[J]. Journal of Mine Automation,2023,49(S1):72-75.
[10]	刘恺. 基于深度强化学习的车辆资源调度与交易算法研究[D]. 成都:电子科技大学,2022. LIU Kai. Research on vehicle resource scheduling and trading algorithm based on deep reinforcement learning[D]. Chengdu:University of Electronic Science and Technology,2022.
[11]	杨华龙,赵亮,靳莉哲,等. 基于汇集预测的随机客户需求配送车辆调度问题[J]. 系统管理学报,2019,28(5):917-926. YANG Hualong,ZHAO Liang,JIN Lizhe,et al. Distribution vehicle scheduling problem based on aggregation and prediction of random customer demands[J]. Journal of Systems & Management,2019,28(5):917-926.
[12]	唐非. 机场地勤服务中特种车辆调度及其优化算法[D]. 沈阳:东北大学,2019. TANG Fei. Special vehicle scheduling and its optimization algorithm in airport ground services[D]. Shenyang:Northeast University,2019.
[13]	包翔宇,单成伟,吴岩明. 基于UWB精确定位的辅助运输交通灯自动控制系统[J]. 工矿自动化,2022,48(6):100-111. BAO Xiangyu,SHAN Chengwei,WU Yanming. Automatic control system of auxiliary transportation traffic light based on UWB precise positioning[J]. Journal of Mine Automation,2022,48(6):100-111.
[14]	胡青松,孟春蕾,李世银,等. 矿井无人驾驶环境感知技术研究现状及展望[J]. 工矿自动化,2023,49(6):128-140. HU Qingsong,MENG Chunlei,LI Shiyin,et al. Research status and prospects of perception technology for unmanned mining vehicle driving environment[J]. Journal of Mine Automation,2023,49(6):128-140.
[15]	曹春玲,李梦雨,张娜齐. 煤矿辅助运输调度系统的层次颜色Petri网建模[J]. 工业工程,2021,24(6):1-7. CAO Chunling,LI Mengyu,ZHANG Naqi. Modeling of hierarchical color Petri net for coal mine auxiliary transportation dispatching system[J]. Industrial Engineering Journal,2021,24(6):1-7.
[16]	李梦雨. 煤矿井下辅助运输车辆调度系统的研究[D]. 西安:西安科技大学,2021. LI Mengyu. Research on reliability of coal mine underground transport system[D]. Xi'an:Xi'an University of Science and Technolog,2021.
[17]	侯成铭. 煤矿井下燃油运输车辆调度多目标优化分析[J]. 兰州工业学院学报,2023,30(2):88-93. HOU Chengming. Multi-objective optimization analysis of fuel transport vehicle scheduling in underground coal mine[J]. Journal of Lanzhou Institute of Technology,2023,30(2):88-93.
[18]	孙莹,连民杰. 基于改进蚁群算法的地下矿车辆生产调度路径优化研究[J]. 金属矿山,2010(2):51-54. SUN Ying,LIAN Minjie. Research on vehicle routing and scheduling problems based on improved ACA in underground mine[J]. Metal Mine,2010(2):51-54.
[19]	王兆锐,林剑,张俊丽,等. 基于车公里成本的多车型车辆规划方法[J]. 物流技术,2019,38(1):82-87. WANG Zhaorui,LIN Jian,ZHANG Junli,et al. Multi-model vehicle scheduling based on per vehicle-kilometer cost[J]. Logistics Technology,2019,38(1):82-87.
[20]	WANG Zhan,LAMBERT A. A low-cost consistent vehicle localization based on interval constraint propagation[J]. Journal of Advanced Transportation,2018. DOI: 10.1155/2018/2713729.
[21]	钟宏扬,彭乘风,廖勇,等. 基于组合规则的作业车间AGV联合调度优化[J]. 制造技术与机床,2022(11):183-192. ZHONG Hongyang,PENG Chengfeng,LIAO Yong,et al. Combined rules based optimization for AGV joint scheduling in job shop[J]. Manufacturing Technology & Machine Tool,2022(11):183-192.