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