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Gold Science and Technology ›› 2019, Vol. 27 ›› Issue (3): 458-465.doi: 10.11872/j.issn.1005-2518.2019.03.458

• Mining Technology and Mine Management • Previous Articles    

Ore Grade Control Blending in Open-pit Mine Based on Mixed Integer Programming

Hongjian TU1,2(),Liguan WANG1,2(),Xin CHEN1,2,Zhuli REN1,2,Ju ZHANG1,2   

  1. 1. School of Resources and Safety Engineering,Central South University,Changsha 410083,Hunan,China
    2. Center of Digital Mine Research,Central South University,Changsha 410083,Hunan,China
  • Received:2018-10-08 Revised:2019-02-22 Online:2019-06-30 Published:2019-07-09
  • Contact: Liguan WANG E-mail:hongjian_tu@163.com;liguan_wang@163.com

Abstract:

Rational planning and management of ore quality is an important issue to improve the resource and economic benefits of the mine.Resources and quality control of ore should be run through all aspects of the entire production management process.In order to solve problems existed in ore blending for open-pit mine,such as long-time ore blending,low accuracy of planned results and not associated with truck dispatching system,the open-pit mine automation ore blending system was proposed.It is based on Mixed Integer Programming and would make the ore grade control in open-pit mine more accurately and rapidly,so rational mining and fine control of production targets for the open-pit mine automation ore blending would be achieved.It was put forward based on the current status quo of stope,exploration engineering data and resource model,on the premise of production quality control,and mixed integer programming algorithm is used as the theoretical method.This paper taking a large limestone open-pit in Anhui Province as research object.In the first place,thiessen polygon method was applied to estimation value and divide the ore blending model based on rock sample of blasthole and mine block model.Then a mixed integer programming model was presented according to the special ore blending requirements of muck piles in open pit mineto solve the optimization problem of ore blending.The model takes the minimum fluctuation of the ore grade as the objective function,and takes into account a variety of constraints,such as the muck sub-piles mining constraint,vehicle dispatching manner constraint,shovel car mining constraint,number of shovel car in each pile constraint,maximum grade of ore dumping constraint,minimum grade of ore dumping constraint .At last,the automatic ore distribution system of open pit mine is established based on iMine spatial database technology with C++ language programming in Visual Studio 2012,by solving the mixed integer programming model of open-pit ore blending by IBM ILOG CPLEX Optimization Studio, the open-pit ore blending optimization scheme of mine and truck dispatching can be achieved.The method was applied to Quanjiao Conch limestone mine,several months of practical application proved that this model is scientific and feasible.The ore blending method can output result in 1 s,and the maximum deviation of each index of ore blending fluctuates from the target value within the range of 1.5%,the average deviation of each index from the target value is less than 0.2%,and the coefficient of variation is less than 1%.It meets the requirement of mine grade deviation control,so it is of important significance for guiding the actual production of open-pit mine.

Key words: open-pit, ore blending, mixed integer programming, grade control, limestone, block model, thiessen polygon method

CLC Number: 

  • TD872

Fig.1

Element model of ore blending"

Fig.2

Flow diagram of ore blending system"

Fig.3

3D geological map of one large limestone mine"

Fig.4

Muck piles distribution map of ore blending"

Table 1

Ore quantity and grade information of muck sub-piles"

爆堆 配矿单元 CaO/% MgO/% R2O SM 矿石量/t
BD2017-150006 01 45.113 0.796 0.262 5.391 5 837.47
BD201709-11227S 01 53.122 0.921 0.145 3.489 16 443.42
02 52.413 0.892 0.137 3.182 14 902.94
BD201709-11229S 01 42.104 2.118 0.753 3.497 12 839.54
02 51.527 1.304 0.174 4.004 5 954.49
03 53.858 0.885 0.119 3.606 16 981.37
? ? ? ? ? ? ?
BD201712-15012M 01 42.345 0.976 0.460 5.742 15 983.21
02 47.474 0.707 0.411 5.143 13 921.77
03 48.417 1.279 0.433 3.285 12 642.13

Table 2

Ore blending scheme"

铲车型号 爆堆 配矿单元 矿石类型 CaO/% MgO/% R2O SM 矿石量/t 铲车/辆
总计 石灰石 46.221 1.480 0.454 3.378 21 110.00 703
01#PC400 BD2017-15006N 01 高硅 45.113 0.796 0.262 5.391 3 040.00 101
02#PC400 BD201712-10009S 01 高镁 44.001 2.507 0.264 3.000 3 300.00 110
03#PC400 BD201712-10014M 01 高镁 37.837 2.623 1.192 2.609 3 360.00 112
05#PC400 BD201712-15012M 03 高钙 48.417 1.279 0.433 3.285 3 360.00 112
CAT988 BD201709-11230S 02 高钙 53.532 0.681 0.116 2.545 4 000.00 133
PC1250 BD201712-10022S 02 泥夹石 46.817 1.185 0.499 3.708 4 050.00 135

Fig.5

Numerical wave diagram of ore blending target"

Fig.6

Coefficient of variance diagram of ore blending"

1 Espinoza D , Goycoolea M , Moreno E ,et al .MineLib:A library of open pit mining problems[J].Annals of Operations Research,2013,206(1):93-114.
2 Rahmanpour M , Osanloo M .Resilient decision making in open pit short-term production planning in presence of geologic uncertainty[J].International Journal of Engineering,Transactions B:Applications,2016,29(7):1022-1028.
3 Caccetta L , Hill S P .An application of branch and cut to open pit mine scheduling[J].Journal of Global Optimization,2003,27(2/3):349-365.
4 Azimi Y , Osanloo M , Esfahanipour A .An uncertainty based multi-criteria ranking system for open pit mining cut-off grade strategy selection[J].Resources Policy,2013,38(2):212-223.
5 Gholamnejad J , Osanloo M .Incorporation of ore grade uncertainty into the push back design process[J].The Journal of the Southern African Institute of Mining and Metallurgy,2007,107(3):177-185.
6 Rahmanpour M , Osanloo M .Determination of value at risk for long-term production planning in open pit mines in the presence of price uncertainty[J].The Journal of the Southern African Institute of Mining and Metallurgy,2016,116(3):229-236.
7 Newman A M , Rubio E , Caro R ,et al .A review of operations research in mine planning[J].Interfaces,2010,40(3):222-245.
8 Osanloo M , Gholamnejad J , Karimi B .Long-term open pit mine production planning:A review of models and algorithms[J].International Journal of Mining,Reclamation and Environment,2008,22(1):3-35.
9 Kumral M , Dowd P A .Adelaide research and scholarship:Short-term mine production scheduling for industrial minerals using multi-objective simulated annealing[C]//Bandopadhyay S.International Symposium on the Application of Computers and Operations Research in the Minerals Industry.Colorado:Society for Mining,Metallurgy and Exploration,2002:731-741.
10 Desaulniers G , Langevin A , Riopel D ,et al .Dispatching and conflict-free routing of automated guided vehicles:An exact approach[J].International Journal of Flexible Manufacturing Systems,2003,15(4):309-331.
11 Asad M W A .Implementing a blending optimization model for short-range production planning of cement quarry operation[J].Journal of Mining Science,2010,46(5):525-535.
12 Souza M J F , Coelho I M , Ribas S ,et al .A hybrid heuristic algorithm for the open-pit-mining operational planning problem[J].European Journal of Operational Research,2010,207(2):1041-1051.
13 Fioroni M M , Franzese L A G , Bianchi T J ,et al .Concurrent simulation and optimization models for mining planning[C]//Proceedings of the 2010 Winter Simulation Conference.New York:IEEE,2008:759-767.
14 Stevanovic D , Kolonja B , Stankovic R ,et al .Application of stochastic models for mine planning and coal quality control[J].Thermal Science,2014,18(4):1361-1372.
15 Shishvan M S , Benndorf J .The effect of geological uncertainty on achieving short-term targets:A quantitative approach using stochastic process simulation[J].Journal of the Southern African Institute of Mining and Metallurgy,2015,116(3):259-264.
16 黄启富,陈建宏 .基于PSO的矿山企业动态配矿优化研究[J].计算机工程,2011,37(8):175-177,180.
Huang Qifu , Chen Jianhong .Research on dynamic mine ore blending optimization based on particle swarm optimization in mining enterprises[J].Computer Engineering,2011,37(8):175-177,180.
17 杨珊,陈建宏,杨海洋,等 .基于Xpress-MP堆积型铝土矿堆场配矿优化研究[J].金属矿山,2010,39(3):9-11.
Yang Shan , Chen Jianhong , Yang Haiyang ,et al .Optimization research of accumulated bauxite ore blending in yard based on Xpress-MP[J].Metal Mine,2010,39(3):9-11.
18 王李管,宋华强,毕林,等 .基于目标规划的露天矿多元素配矿优化[J].东北大学学报(自然科学版),2017,38(7):1031-1036.
Wang Liguan , Song Huaqiang , Bi Lin ,et al .Optimization of open pit multielement ore blending based on goal programming[J].Journal of Northeastern University(Natural Science),2017,38(7):1031-1036.
19 吴丽春,王李管,彭平安,等 .露天矿配矿优化方法研究[J].矿冶工程,2012,32(4):8-12.
Wu Lichun , Wang Liguan , Peng Ping’an ,et al .Optimization methods for ore blending in open-pit mine[J].Mining and Metallurgical Engineering,2012,32(4):8-12.
20 任助理,毕林,王李管,等 .基于混合整数规划法的自然崩落法放矿计划优化[J].工程科学学报,2017,39(1):23-30.
Ren Zhuli , Bi Lin , Wang Liguan ,et al .Optimization of drawing scheduling based on mixed integer programming in block cave mining[J].Chinese Journal of Engineering,2017,39(1):23-30.
21 Rodrigo M , Enrico Z , Fredy K ,et al .Availability-based simulation and optimization modeling framework for open-pit mine truck allocation under dynamic constraints[J].International Journal of Mining Science and Technology,2013,23(1):113-119.
22 Coelho V N , Souza M J F , Coelho I M ,et al .Multi-objective approaches for the open-pit mining operational planning problem[J].Electronic Notes in Discrete Mathematics,2012,39(2):233-240.
23 Du D Z , Frank H .Computing In Euclidean Geometry[M].Evanston:World Scientific,1992.
24 Boissonnat J D , Nielsen F , Nock R .On bregman voronoi diagrams[J].Discrete and Computational Geometry,2010,44(2):281-307.
25 陈丽,胡乃联 .基于Voronoi图的爆区品位和矿量计算[J].爆破,2011,28(2):39-41.
Chen Li , Hu Nailian .Method of calculating ore grade and quantity of blast zone based on Voronoi diagram[J].Blasting,2011,28(2):39-41.
26 杨桦,胡乃联,孙晓,等 .基于炮孔化验数据的资源模型动态更新技术研究[J].矿业研究与开发,2013,33(2):105-109.
Yang Hua , Hu Nailian , Sun Xiao ,et al .Dynamic update technology of geological resource model based on blasthole data[J].Mining Research and Development,2013,33(2):105-109.
27 Ghasemi E , Amnieh H B , Bagherpour R .Assessment of backbreak due to blasting operation in open pit mines:A case study[J].Environmental Earth Sciences,2016,75(7):552-558.
28 Bye A .The strategic and tactical value of a 3D geotechnical model for mining optimization,Anglo Platinum,Sandsloot open pit[J].The Journal of the South African Institute of Mining and Metallurgy,2006,106(4):97-104.
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