地下矿床开拓系统空间优化的粒子群方法
摘要
矿床开拓系统是矿山建设的灵魂,关系到矿床开采运输和主体井巷布置,开拓系统的空间状态和行为是优化设计的重要内容之一,设计必须综合考虑井巷基建、矿石运输和工程地质环境优劣等多重复杂因素。传统的矿床开拓系统的优化多依靠专家经验定性分析或复杂的技术经济分析。为此,当前国内外展开了应用优化理论方法进行矿床开拓系统的定量评价及优化设计研究。
本研究提出将矿石由各采场采出逆向考虑为矿石物流配送问题,转换为车辆路径问题物理模型的研究新思路；基于ARCGIS空间分析平台、Matlab算法平台实现演绎的方法模型,可以解决车辆路径问题等复杂的组合优化问题,为开拓系统优化提供技术支持。
对已有的初步设计中提出的几套开拓系统,对其投影叠加形成开拓系统网络图,这样矿石运输在网络图上表现为地表出口至采场配送运输的行为,是典型的车辆路径研究问题。开拓系统优化的目的在于：以开拓系统的掘进费用、支护费用和运输费用为评价因子,在网络图中寻找满足矿石配送任务要求的最优路径组合。
定量模型研究方面,车辆路径问题研究包含空间状态和行为两方面,矿床开拓问题研究中,就是对开拓井巷布置和矿石运输路径同时进行优化,涉及状态和行为两种不同的影响因素,传统精确算法无法穷举求解。本研究采用群智能粒子群算法(PSO)搜索车辆路径问题满意解,考虑车辆路径组合时两采场间存在多路径选择问题,引入Dijkstra搜索最短路径实现两采场之间路径单一化,构建解决开拓系统优化车辆路径问题的数学模型。
技术实现上,在数学模型构建的基础上,基于GIS平台实现开拓系统网络图矢量化的空间表达,并建立拓扑关系,赋予属性数据；依托Matlab平台开发PSO和Dijkstra混合算法,将数据转换后以数据表格式导入Matlab进行优化计算；优化结果经数据转换后反馈至GIS平台进行空间和属性表达。
研究以湖北省某铜矿开拓系统为实例进行试验,优化得到的井巷布置与矿山当前选用设计方案空间布局整体一致,证明优化结果符合开拓实际；通过成本比较,优化后开拓运输成本较设计概预算节约10%。研究表明把矿床开拓系统优化作为车辆路径问题求解是可行的,有研究和实践价值；论文给出了优化算法程序实现流程和代码,对包含多路径选择的复杂车辆路径问题解决有参考价值。
Ore Deposit development system is the core of the mining construction, which is related to deposit mining transport and the main roadway layout. The optimal design of Ore Deposit development system must study the space status and behavior of development system and consider of multiple complex factors synthetically, such as the roadway capital construction, ore transportation and engineering geological environmental quality. The traditional optimization of Ore Deposit development system mainly relies on the expert's experience on qualitative analysis or complex technical and economic analysis. Therefore, nowadays scholars both domestic and abroad apply optimization theory into quantitative evaluation and optimization of deposits development system.
This paper take each stope as ore few logistics distribution problems, namely transfers as vehicle routing problem model, which provides new ideas for the development system optimization. Based on GIS spatial analysis platform, combining space information technology with artificial intelligence optimization algorithm, it can solve the complex combinatorial optimization problem, such as the vehicle routing problem, which provides technical support to explore the system optimization.
According to the preliminary designs of development system, projecting and overlapping these to form the development system network diagram, Ore transportation is defined as transporting from exit of the distribution to the stope. The purpose of development system optimization is to find the optimal distribution path combinations in the network diagram, which can meet the mission requirements of ore, based on exploring system's driving costs, support costs and transportation costs as the evaluation factors.
In quantitative model, the study of constructing the vehicle routing problem including space status and behavior, to optimize development roadway layout and ore transportation path simultaneously, It is involved with two kinds of different factors, and becoming more complex, so traditional accurate algorithm can't be an exhaustively solution. This study adopts particle swarm optimization (PSO) to search the satisfactory solution of vehicle routing problems. when considering vehicle routing combination between the two mining sites, there will be multiple selections of paths, so this paper introduces Dijkstra to search the shortest path between two mining sites and realizes path simplification by constructing mathematical model of vehicle routing problem of development system
In technology realization, based on mathematical model and GIS platform, it needs to realize the vector expression of pioneering system network diagram, to establish the space of topological relationships and then give attribute data; Relying on Matlab platform to development the PSO-Dijkstra hybrid algorithm, then transferring the data into data form and put into Matlab to start the optimized calculation; The final result data will be transferred and re-fed back to the GIS platform for spatial and attribute expression.
This paper takes the development system of a copper mine in Hubei Province as an example. The optimization result is mainly in accord with the current mining design on space layout, which proves that the optimization results conform to exploit reality. By costs comparison, the costs of optimized design of development transportation can be saved more than 10%. Result shows that it's feasible to solve the problem in vehicle routing optimization way and it has some practical significance. This paper puts out the optimization algorithm program realization process and code, which has some reference value for solving complex vehicle routing problems containing multi-path selection.
本研究提出将矿石由各采场采出逆向考虑为矿石物流配送问题,转换为车辆路径问题物理模型的研究新思路；基于ARCGIS空间分析平台、Matlab算法平台实现演绎的方法模型,可以解决车辆路径问题等复杂的组合优化问题,为开拓系统优化提供技术支持。
对已有的初步设计中提出的几套开拓系统,对其投影叠加形成开拓系统网络图,这样矿石运输在网络图上表现为地表出口至采场配送运输的行为,是典型的车辆路径研究问题。开拓系统优化的目的在于：以开拓系统的掘进费用、支护费用和运输费用为评价因子,在网络图中寻找满足矿石配送任务要求的最优路径组合。
定量模型研究方面,车辆路径问题研究包含空间状态和行为两方面,矿床开拓问题研究中,就是对开拓井巷布置和矿石运输路径同时进行优化,涉及状态和行为两种不同的影响因素,传统精确算法无法穷举求解。本研究采用群智能粒子群算法(PSO)搜索车辆路径问题满意解,考虑车辆路径组合时两采场间存在多路径选择问题,引入Dijkstra搜索最短路径实现两采场之间路径单一化,构建解决开拓系统优化车辆路径问题的数学模型。
技术实现上,在数学模型构建的基础上,基于GIS平台实现开拓系统网络图矢量化的空间表达,并建立拓扑关系,赋予属性数据；依托Matlab平台开发PSO和Dijkstra混合算法,将数据转换后以数据表格式导入Matlab进行优化计算；优化结果经数据转换后反馈至GIS平台进行空间和属性表达。
研究以湖北省某铜矿开拓系统为实例进行试验,优化得到的井巷布置与矿山当前选用设计方案空间布局整体一致,证明优化结果符合开拓实际；通过成本比较,优化后开拓运输成本较设计概预算节约10%。研究表明把矿床开拓系统优化作为车辆路径问题求解是可行的,有研究和实践价值；论文给出了优化算法程序实现流程和代码,对包含多路径选择的复杂车辆路径问题解决有参考价值。
Ore Deposit development system is the core of the mining construction, which is related to deposit mining transport and the main roadway layout. The optimal design of Ore Deposit development system must study the space status and behavior of development system and consider of multiple complex factors synthetically, such as the roadway capital construction, ore transportation and engineering geological environmental quality. The traditional optimization of Ore Deposit development system mainly relies on the expert's experience on qualitative analysis or complex technical and economic analysis. Therefore, nowadays scholars both domestic and abroad apply optimization theory into quantitative evaluation and optimization of deposits development system.
This paper take each stope as ore few logistics distribution problems, namely transfers as vehicle routing problem model, which provides new ideas for the development system optimization. Based on GIS spatial analysis platform, combining space information technology with artificial intelligence optimization algorithm, it can solve the complex combinatorial optimization problem, such as the vehicle routing problem, which provides technical support to explore the system optimization.
According to the preliminary designs of development system, projecting and overlapping these to form the development system network diagram, Ore transportation is defined as transporting from exit of the distribution to the stope. The purpose of development system optimization is to find the optimal distribution path combinations in the network diagram, which can meet the mission requirements of ore, based on exploring system's driving costs, support costs and transportation costs as the evaluation factors.
In quantitative model, the study of constructing the vehicle routing problem including space status and behavior, to optimize development roadway layout and ore transportation path simultaneously, It is involved with two kinds of different factors, and becoming more complex, so traditional accurate algorithm can't be an exhaustively solution. This study adopts particle swarm optimization (PSO) to search the satisfactory solution of vehicle routing problems. when considering vehicle routing combination between the two mining sites, there will be multiple selections of paths, so this paper introduces Dijkstra to search the shortest path between two mining sites and realizes path simplification by constructing mathematical model of vehicle routing problem of development system
In technology realization, based on mathematical model and GIS platform, it needs to realize the vector expression of pioneering system network diagram, to establish the space of topological relationships and then give attribute data; Relying on Matlab platform to development the PSO-Dijkstra hybrid algorithm, then transferring the data into data form and put into Matlab to start the optimized calculation; The final result data will be transferred and re-fed back to the GIS platform for spatial and attribute expression.
This paper takes the development system of a copper mine in Hubei Province as an example. The optimization result is mainly in accord with the current mining design on space layout, which proves that the optimization results conform to exploit reality. By costs comparison, the costs of optimized design of development transportation can be saved more than 10%. Result shows that it's feasible to solve the problem in vehicle routing optimization way and it has some practical significance. This paper puts out the optimization algorithm program realization process and code, which has some reference value for solving complex vehicle routing problems containing multi-path selection.
引文
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[2]梁宵,袁艳斌,张帆等.数字矿山应用及其现状研究[J].中国矿业,2010(9)：94-97.
[3]古德生,李夕兵,现代金属矿床开采科学技术[M].北京：冶金工业出版社,2006
[4]周华.蚁群算法在开拓系统结构优化中的应用研究[D].西安建筑科技大学,硕士学位论文,2005.
[5]田金华,李栋祥,徐建荣.开拓系统优化选择的灰色局势决策[J].矿业研究与开发,2003(5)：20-22.
[6]周华,卢才武.基于蚁群算法的矿山井下开拓系统优化研究[J].建井技术,2005(2)33-36.
[7]赵向东.开拓与回采巷道优化布局的技术经济研究[J].黑龙江科技信息,2010(27)255-256.
[8]聂兴信,陈永锋,卢才武.遗传算法在露天矿开拓系统优化中的应用[J].金属矿山,2007(2)：19-22.
[9]罗传兴.基于模糊灰色理论的采矿方法选择[J].采矿技术,2010,10(2)：7-8.
[10]田金华,池秀文,马俊生.模糊层次分析法在金刚石矿开拓系统优化选择中的应用[J].矿业工程,2003(5)：26-28.
[11]Yuan Yan-bin, Liang Xiao, Huang Jiejunet al, Geological Anomaly Mining in Mineralization Based on Rough Set[C],2009:581-585.
[12]张世雄,蒋国安,固体矿物资源开发工程[M].武汉：武汉理工大学出版社,2005
[13]卢少华.遗传规划及其在采切巷道结构性优化中的应用研究[D].西安建筑科技大学,硕士学位论文,2001.
[14]王青,史维祥,采矿学[M]：冶金工业出版社,2001
[15]刘岳军.宝山矿西区深部开拓运输系统选择[J].采矿技术,2010(3)：38-39.
[16]袁艳斌,梁宵,张晓盼等.矿山运输系统可靠性的熵权法模糊综合评判[J].金属矿山,2011(2)：28-31.
[17]解世俊,金属矿床地下开采[M]：冶金工业出版社,1979
[18]云庆夏,黄凯明.确定地下矿开拓系统的遗传算法[J].金属矿山,2001(2)：16-19.
[19]刘伟洁,张钦礼,王新民.基于DEA模型的露天转地下竖井开拓方案优选[J].金属矿山,2010(4)：28-31.
[20]吕福军.龙口矿区“三软”矿井分区域开拓优化与实践[D].东北大学,硕士学位论文,2003.
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