A new risk-based optimisation method for the iron ore production scheduling using stochastic integer programming

Stochastic integer programming (SIP) has recently been studied to manage the risk caused by geological uncertainty when solving mine planning and production scheduling problems of open pit mines. However, similar to other mathematical programming techniques that deploy integer variables, the main ob...

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Vydáno v:	Resources policy Ročník 62; s. 571 - 579
Hlavní autoři:	Mai, Ngoc Luan, Topal, Erkan, Erten, Oktay, Sommerville, Bruce
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Kidlington Elsevier Ltd 01.08.2019 Elsevier Science Ltd
Témata:	Aggregate data Algorithms Case studies Computer simulation Datasets Integer programming Integers Iron and steel making Iron compounds Iron ore production scheduling Iron ores Large-scale optimisation Mathematical programming Mineral deposits Mining Mining industry Open pit mining Optimization Ores Present value Production Production scheduling Risk Risk management Stochastic integer programming TopCone algorithm Uncertainty Variables Large-scale optimisation Open pit mining TopCone algorithm Iron ore production scheduling Stochastic integer programming
ISSN:	0301-4207, 1873-7641
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Abstract	Stochastic integer programming (SIP) has recently been studied to manage the risk caused by geological uncertainty when solving mine planning and production scheduling problems of open pit mines. However, similar to other mathematical programming techniques that deploy integer variables, the main obstacle of applying SIP on real-life datasets stems from the enormous number of integer variables required by its mathematical formulation, which is a function of number of mining blocks being processed and lifespan of the mining project. In this paper, a new framework is proposed for stochastic mine planning process which makes the application of SIP on large-scale datasets tractable. Firstly, mining blocks of simulated orebody models are clustered using TopCone algorithm to significantly reduce the scale of the data. A new SIP model is then developed to work on aggregated blocks so not only the net present value (NPV) is maximised and the risk of not meeting production targets is minimised, but also solution can be obtained in a practical timeframe. The scheduling result of the new SIP model is also compared to an integer programming (IP) model to highlight the ability to manage risk and generating higher NPV on a case study of a large-scale multi-element iron ore deposit in Pilbara region, Western Australia. •We develop a new risk-based optimisation method for iron ore production scheduling.•We use stochastic integer programming and a block aggregation technique called TopCone algorithm.•A case study in an iron ore deposit in Pilbara region, Western Australia shows a considerable increase of NPV and risk reduction.•The solution is achieved in a practical timeframe using a standard office computer.
AbstractList	Stochastic integer programming (SIP) has recently been studied to manage the risk caused by geological uncertainty when solving mine planning and production scheduling problems of open pit mines. However, similar to other mathematical programming techniques that deploy integer variables, the main obstacle of applying SIP on real-life datasets stems from the enormous number of integer variables required by its mathematical formulation, which is a function of number of mining blocks being processed and lifespan of the mining project. In this paper, a new framework is proposed for stochastic mine planning process which makes the application of SIP on large-scale datasets tractable. Firstly, mining blocks of simulated orebody models are clustered using TopCone algorithm to significantly reduce the scale of the data. A new SIP model is then developed to work on aggregated blocks so not only the net present value (NPV) is maximised and the risk of not meeting production targets is minimised, but also solution can be obtained in a practical timeframe. The scheduling result of the new SIP model is also compared to an integer programming (IP) model to highlight the ability to manage risk and generating higher NPV on a case study of a large-scale multi-element iron ore deposit in Pilbara region, Western Australia. Stochastic integer programming (SIP) has recently been studied to manage the risk caused by geological uncertainty when solving mine planning and production scheduling problems of open pit mines. However, similar to other mathematical programming techniques that deploy integer variables, the main obstacle of applying SIP on real-life datasets stems from the enormous number of integer variables required by its mathematical formulation, which is a function of number of mining blocks being processed and lifespan of the mining project. In this paper, a new framework is proposed for stochastic mine planning process which makes the application of SIP on large-scale datasets tractable. Firstly, mining blocks of simulated orebody models are clustered using TopCone algorithm to significantly reduce the scale of the data. A new SIP model is then developed to work on aggregated blocks so not only the net present value (NPV) is maximised and the risk of not meeting production targets is minimised, but also solution can be obtained in a practical timeframe. The scheduling result of the new SIP model is also compared to an integer programming (IP) model to highlight the ability to manage risk and generating higher NPV on a case study of a large-scale multi-element iron ore deposit in Pilbara region, Western Australia. •We develop a new risk-based optimisation method for iron ore production scheduling.•We use stochastic integer programming and a block aggregation technique called TopCone algorithm.•A case study in an iron ore deposit in Pilbara region, Western Australia shows a considerable increase of NPV and risk reduction.•The solution is achieved in a practical timeframe using a standard office computer.
Author	Sommerville, Bruce Mai, Ngoc Luan Topal, Erkan Erten, Oktay
Author_xml	– sequence: 1 givenname: Ngoc Luan surname: Mai fullname: Mai, Ngoc Luan email: ngocluan.mai@postgrad.curtin.edu.au organization: Western Australian School of Mines, Curtin University, Bentley, WA 6102, Australia – sequence: 2 givenname: Erkan surname: Topal fullname: Topal, Erkan email: E.Topal@curtin.edu.au organization: Western Australian School of Mines, Curtin University, Bentley, WA 6102, Australia – sequence: 3 givenname: Oktay orcidid: 0000-0002-1718-3400 surname: Erten fullname: Erten, Oktay email: oktay.erten@curtin.edu.au organization: Western Australian School of Mines, Curtin University, Bentley, WA 6102, Australia – sequence: 4 givenname: Bruce surname: Sommerville fullname: Sommerville, Bruce email: Bruce.Sommerville2@riotinto.com organization: Rio Tinto, Perth, WA 6000, Australia
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Cites_doi	10.1134/S1062739149010097 10.1287/opre.1120.1050 10.1504/IJMME.2011.042429 10.1016/j.asoc.2015.01.060 10.1080/09208119908944244 10.1080/17480930.2011.600827 10.1134/S1062739147020080 10.1134/S1062739147020018 10.1016/j.ejor.2005.12.035 10.1179/mnt.2002.111.1.82 10.17159/2411-9717/2018/v118n7a4 10.1016/j.ejor.2012.05.029 10.1016/j.resourpol.2013.01.004 10.1016/j.resourpol.2013.09.008 10.1179/1743286311Y.0000000009 10.1023/A:1007570402430 10.1023/A:1024835022186 10.1007/s11004-012-9402-9 10.1007/s11081-012-9186-2 10.1179/1743286311Y.0000000018 10.1179/174328607X228848
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References	Azimi, Osanloo, Esfahanipour (bib2) 2013; 38 Dimitrakopoulos (bib11) 2011; 47 Sandanayake, Topal, Asad (bib31) 2015; 30 Topal, Ramazan (bib36) 2012; 26 Leite, Dimitrakopoulos (bib21) 2007; 116 Ravenscroft (bib30) 1992; 101 Mai, Erten, Topal (bib24) 2016 Lamghari, Dimitrakopoulos (bib20) 2012; 222 Mai, Topal, Erten (bib25) 2018; 118 Ramazan, Dimitrakopoulos (bib27) 2004; 316 Caccetta, Hill (bib7) 2003; 27 Groeneveld, Topal, Leenders (bib18) 2012; 121 Ramazan (bib26) 2007; 177 Desbarats, Dimitrakopoulos (bib10) 2000; 32 Bleines, C., de Paris, E.d.M., 2000. Little, Topal (bib22) 2011; 3 Benndorf, Dimitrakopoulos (bib4) 2013; 49 Erten, O., Kizil, M.S., Beamish, B.B., McAndrew, L., 2011. Groeneveld, Topal (bib17) 2011; 47 Baker, C., Giacomo, S., 1998. Godoy, Dimitrakopoulos (bib15) 2004; 316 Denby, Schofield (bib9) 1994; 103 Tabesh, Askari-Nasab (bib33) 2011; 120 Paper presented at the Computer applications in the minerals industries. International Symposium. Mai, Erten, Topal (bib23) 2016 Tolwinski, B., 1998. Chicoisne, Espinoza, Goycoolea, Moreno, Rubio (bib8) 2012; 60 Boucher, Dimitrakopoulos (bib6) 2012; 44 Asad, Dimitrakopoulos (bib1) 2013; 38 Paper presented at the Ore Reserves and Finance: A Joint Seminar between Australasian Institute of Mining and Metallurgy and ASX. Paper presented at the 22nd International Mining Congress and Exhibition of Turkey-IMCET. Geovariances and Ecole des Mines de Paris. Ramazan, Dimitrakopoulos (bib28) 2007 Dowd, P., 1994. Risk assessment in reserve estimation and open-pit planning. . Ramazan, Dimitrakopoulos (bib29) 2013; 14 Goodfellow (bib16) 2014 Vallee (bib37) 2000; 93 Smith, Dimitrakopoulos (bib32) 1999; 13 Topal (bib35) 2008; 108 Jélvez, Morales, Nancel-Penard, Peypouquet, Reyes (bib19) 2015 Dimitrakopoulos, Farrelly, Godoy (bib12) 2002; 111 Azimi (10.1016/j.resourpol.2018.11.004_bib2) 2013; 38 Groeneveld (10.1016/j.resourpol.2018.11.004_bib17) 2011; 47 Groeneveld (10.1016/j.resourpol.2018.11.004_bib18) 2012; 121 Tabesh (10.1016/j.resourpol.2018.11.004_bib33) 2011; 120 Caccetta (10.1016/j.resourpol.2018.11.004_bib7) 2003; 27 Desbarats (10.1016/j.resourpol.2018.11.004_bib10) 2000; 32 Benndorf (10.1016/j.resourpol.2018.11.004_bib4) 2013; 49 10.1016/j.resourpol.2018.11.004_bib13 Chicoisne (10.1016/j.resourpol.2018.11.004_bib8) 2012; 60 10.1016/j.resourpol.2018.11.004_bib14 Leite (10.1016/j.resourpol.2018.11.004_bib21) 2007; 116 Mai (10.1016/j.resourpol.2018.11.004_bib24) 2016 Ravenscroft (10.1016/j.resourpol.2018.11.004_bib30) 1992; 101 Dimitrakopoulos (10.1016/j.resourpol.2018.11.004_bib11) 2011; 47 Lamghari (10.1016/j.resourpol.2018.11.004_bib20) 2012; 222 Smith (10.1016/j.resourpol.2018.11.004_bib32) 1999; 13 Sandanayake (10.1016/j.resourpol.2018.11.004_bib31) 2015; 30 Topal (10.1016/j.resourpol.2018.11.004_bib36) 2012; 26 Topal (10.1016/j.resourpol.2018.11.004_bib35) 2008; 108 Denby (10.1016/j.resourpol.2018.11.004_bib9) 1994; 103 Godoy (10.1016/j.resourpol.2018.11.004_bib15) 2004; 316 Jélvez (10.1016/j.resourpol.2018.11.004_bib19) 2015 Dimitrakopoulos (10.1016/j.resourpol.2018.11.004_bib12) 2002; 111 Little (10.1016/j.resourpol.2018.11.004_bib22) 2011; 3 Ramazan (10.1016/j.resourpol.2018.11.004_bib27) 2004; 316 Vallee (10.1016/j.resourpol.2018.11.004_bib37) 2000; 93 10.1016/j.resourpol.2018.11.004_bib34 Ramazan (10.1016/j.resourpol.2018.11.004_bib26) 2007; 177 10.1016/j.resourpol.2018.11.004_bib3 Goodfellow (10.1016/j.resourpol.2018.11.004_bib16) 2014 Mai (10.1016/j.resourpol.2018.11.004_bib25) 2018; 118 10.1016/j.resourpol.2018.11.004_bib5 Ramazan (10.1016/j.resourpol.2018.11.004_bib29) 2013; 14 Ramazan (10.1016/j.resourpol.2018.11.004_bib28) 2007 Asad (10.1016/j.resourpol.2018.11.004_bib1) 2013; 38 Boucher (10.1016/j.resourpol.2018.11.004_bib6) 2012; 44 Mai (10.1016/j.resourpol.2018.11.004_bib23) 2016
References_xml	– reference: Dowd, P., 1994. Risk assessment in reserve estimation and open-pit planning. – volume: 222 start-page: 642 year: 2012 end-page: 652 ident: bib20 article-title: A diversified Tabu search approach for the open-pit mine production scheduling problem with metal uncertainty publication-title: Eur. J. Oper. Res. – start-page: 385 year: 2007 end-page: 391 ident: bib28 article-title: Stochastic optimisation of long-term production scheduling for open pit mines with a new integer programming formulation. publication-title: Australas. Inst. Min. Metall., Melb. – volume: 316 year: 2004 ident: bib15 article-title: Managing risk and waste mining in long-term production scheduling of open-pit mines publication-title: SME Trans. – volume: 103 year: 1994 ident: bib9 article-title: Open-pit design and scheduling by use of genetic algorithms. publication-title: Sect. A. Min. Ind. – volume: 26 start-page: 29 year: 2012 end-page: 37 ident: bib36 article-title: Strategic mine planning model using network flow model and real case application publication-title: Int. J. Min., Reclam. Environ. – reference: Erten, O., Kizil, M.S., Beamish, B.B., McAndrew, L., 2011. – volume: 47 start-page: 212 year: 2011 end-page: 226 ident: bib17 article-title: Flexible open-pit mine design under uncertainty publication-title: J. Min. Sci. – volume: 93 start-page: 53 year: 2000 end-page: 61 ident: bib37 article-title: Mineral resource+ engineering, economic and legal feasibility publication-title: CIM Bull. – volume: 120 start-page: 158 year: 2011 end-page: 169 ident: bib33 article-title: Two-stage clustering algorithm for block aggregation in open pit mines publication-title: Min. Technol. – volume: 177 start-page: 1153 year: 2007 end-page: 1166 ident: bib26 article-title: The new fundamental tree algorithm for production scheduling of open pit mines publication-title: Eur. J. Oper. Res. – reference: . Paper presented at the 22nd International Mining Congress and Exhibition of Turkey-IMCET. – volume: 316 year: 2004 ident: bib27 article-title: Recent applications of operations research and efficient MIP formulations in open pit mining publication-title: Soc. Min., Metall., Explor., Inc. Trans. – reference: Bleines, C., de Paris, E.d.M., 2000. – reference: Tolwinski, B., 1998. – volume: 3 start-page: 152 year: 2011 end-page: 172 ident: bib22 article-title: Strategies to assist in obtaining an optimal solution for an underground mine planning problem using Mixed Integer Programming publication-title: Int. J. Min. Mineral. Eng. – volume: 14 start-page: 361 year: 2013 end-page: 380 ident: bib29 article-title: Production scheduling with uncertain supply: a new solution to the open pit mining problem publication-title: Optim. Eng. – reference: . Paper presented at the Computer applications in the minerals industries. International Symposium. – volume: 44 start-page: 449 year: 2012 end-page: 468 ident: bib6 article-title: Multivariate block-support simulation of the Yandi iron ore deposit, Western Australia publication-title: Math. Geosci. – reference: . Paper presented at the Ore Reserves and Finance: A Joint Seminar between Australasian Institute of Mining and Metallurgy and ASX. – volume: 47 start-page: 138 year: 2011 end-page: 150 ident: bib11 article-title: Stochastic optimization for strategic mine planning: a decade of developments publication-title: J. Min. Sci. – volume: 49 start-page: 68 year: 2013 end-page: 81 ident: bib4 article-title: Stochastic long-term production scheduling of iron ore deposits: integrating joint multi-element geological uncertainty publication-title: J. Min. Sci. – reference: : Geovariances and Ecole des Mines de Paris. – start-page: 577 year: 2016 end-page: 582 ident: bib23 article-title: Joint Conditional Simulation of an Iron Ore Deposit Using Minimum or Maximum Autocorrelation Factor Transformation publication-title: Geostatistical and Geospatial Approaches for the Characterization of Natural Resources in the Environment – volume: 32 start-page: 919 year: 2000 end-page: 942 ident: bib10 article-title: Geostatistical simulation of regionalized pore-size distributions using min/max autocorrelation factors publication-title: Math. Geol. – year: 2015 ident: bib19 article-title: Aggregation heuristic for the open-pit block scheduling problem publication-title: Eur. J. Oper. Res. – volume: 38 start-page: 591 year: 2013 end-page: 597 ident: bib1 article-title: A heuristic approach to stochastic cutoff grade optimization for open pit mining complexes with multiple processing streams publication-title: Resour. Policy – reference: Baker, C., Giacomo, S., 1998. – year: 2014 ident: bib16 article-title: Unified Modelling and Simultaneous Optimization of Open Pit Mining Complexes with Supply Uncertainty – volume: 38 start-page: 212 year: 2013 end-page: 223 ident: bib2 article-title: An uncertainty based multi-criteria ranking system for open pit mining cut-off grade strategy selection publication-title: Resour. Policy – reference: . – volume: 108 start-page: 99 year: 2008 ident: bib35 article-title: Early start and late start algorithms to improve the solution time for long-term underground mine production scheduling publication-title: J. South Afr. Inst. Min. Metall. – start-page: 1 year: 2016 end-page: 11 ident: bib24 article-title: A new generic open pit mine planning process with risk assessment ability publication-title: Int. J. Coal Sci. Technol. – volume: 27 start-page: 349 year: 2003 end-page: 365 ident: bib7 article-title: An application of branch and cut to open pit mine scheduling publication-title: J. Glob. Optim. – volume: 101 year: 1992 ident: bib30 article-title: Risk analysis for mine scheduling by conditional simulation. publication-title: Sect. A. Min. Ind. – volume: 116 start-page: 109 year: 2007 end-page: 118 ident: bib21 article-title: Stochastic optimisation model for open pit mine planning: application and risk analysis at copper deposit publication-title: Min. Technol. – volume: 30 start-page: 595 year: 2015 end-page: 603 ident: bib31 article-title: A heuristic approach to optimal design of an underground mine stope layout publication-title: Appl. Soft Comput. – volume: 60 start-page: 517 year: 2012 end-page: 528 ident: bib8 article-title: A new algorithm for the open-pit mine production scheduling problem publication-title: Oper. Res. – volume: 118 year: 2018 ident: bib25 article-title: A new open-pit mine planning optimization method using block aggregation and integer programming publication-title: J. South. Afr. Inst. Min. Metall. – volume: 13 start-page: 173 year: 1999 end-page: 178 ident: bib32 article-title: The influence of deposit uncertainty on mine production scheduling publication-title: Int. J. Surf. Min., Reclam. Environ. – volume: 121 start-page: 20 year: 2012 end-page: 28 ident: bib18 article-title: Robust, flexible and operational mine design strategies publication-title: Min. Technol. – volume: 111 start-page: 82 year: 2002 end-page: 88 ident: bib12 article-title: Moving forward from traditional optimization: grade uncertainty and risk effects in open-pit design publication-title: Min. Technol. – volume: 49 start-page: 68 issue: 1 year: 2013 ident: 10.1016/j.resourpol.2018.11.004_bib4 article-title: Stochastic long-term production scheduling of iron ore deposits: integrating joint multi-element geological uncertainty publication-title: J. Min. Sci. doi: 10.1134/S1062739149010097 – volume: 60 start-page: 517 issue: 3 year: 2012 ident: 10.1016/j.resourpol.2018.11.004_bib8 article-title: A new algorithm for the open-pit mine production scheduling problem publication-title: Oper. Res. doi: 10.1287/opre.1120.1050 – volume: 3 start-page: 152 issue: 2 year: 2011 ident: 10.1016/j.resourpol.2018.11.004_bib22 article-title: Strategies to assist in obtaining an optimal solution for an underground mine planning problem using Mixed Integer Programming publication-title: Int. J. Min. Mineral. Eng. doi: 10.1504/IJMME.2011.042429 – volume: 30 start-page: 595 year: 2015 ident: 10.1016/j.resourpol.2018.11.004_bib31 article-title: A heuristic approach to optimal design of an underground mine stope layout publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2015.01.060 – volume: 13 start-page: 173 issue: 4 year: 1999 ident: 10.1016/j.resourpol.2018.11.004_bib32 article-title: The influence of deposit uncertainty on mine production scheduling publication-title: Int. J. Surf. Min., Reclam. Environ. doi: 10.1080/09208119908944244 – volume: 26 start-page: 29 issue: 1 year: 2012 ident: 10.1016/j.resourpol.2018.11.004_bib36 article-title: Strategic mine planning model using network flow model and real case application publication-title: Int. J. Min., Reclam. Environ. doi: 10.1080/17480930.2011.600827 – volume: 47 start-page: 212 issue: 2 year: 2011 ident: 10.1016/j.resourpol.2018.11.004_bib17 article-title: Flexible open-pit mine design under uncertainty publication-title: J. Min. Sci. doi: 10.1134/S1062739147020080 – start-page: 1 year: 2016 ident: 10.1016/j.resourpol.2018.11.004_bib24 article-title: A new generic open pit mine planning process with risk assessment ability publication-title: Int. J. Coal Sci. Technol. – volume: 101 year: 1992 ident: 10.1016/j.resourpol.2018.11.004_bib30 article-title: Risk analysis for mine scheduling by conditional simulation. Transactions of the institution of mining and metallurgy publication-title: Sect. A. Min. Ind. – ident: 10.1016/j.resourpol.2018.11.004_bib14 – volume: 108 start-page: 99 issue: 2 year: 2008 ident: 10.1016/j.resourpol.2018.11.004_bib35 article-title: Early start and late start algorithms to improve the solution time for long-term underground mine production scheduling publication-title: J. South Afr. Inst. Min. Metall. – volume: 47 start-page: 138 issue: 2 year: 2011 ident: 10.1016/j.resourpol.2018.11.004_bib11 article-title: Stochastic optimization for strategic mine planning: a decade of developments publication-title: J. Min. Sci. doi: 10.1134/S1062739147020018 – volume: 316 year: 2004 ident: 10.1016/j.resourpol.2018.11.004_bib27 article-title: Recent applications of operations research and efficient MIP formulations in open pit mining publication-title: Soc. Min., Metall., Explor., Inc. Trans. – ident: 10.1016/j.resourpol.2018.11.004_bib3 – volume: 177 start-page: 1153 issue: 2 year: 2007 ident: 10.1016/j.resourpol.2018.11.004_bib26 article-title: The new fundamental tree algorithm for production scheduling of open pit mines publication-title: Eur. J. Oper. Res. doi: 10.1016/j.ejor.2005.12.035 – volume: 111 start-page: 82 issue: 1 year: 2002 ident: 10.1016/j.resourpol.2018.11.004_bib12 article-title: Moving forward from traditional optimization: grade uncertainty and risk effects in open-pit design publication-title: Min. Technol. doi: 10.1179/mnt.2002.111.1.82 – ident: 10.1016/j.resourpol.2018.11.004_bib5 – year: 2015 ident: 10.1016/j.resourpol.2018.11.004_bib19 article-title: Aggregation heuristic for the open-pit block scheduling problem publication-title: Eur. J. Oper. Res. – volume: 118 year: 2018 ident: 10.1016/j.resourpol.2018.11.004_bib25 article-title: A new open-pit mine planning optimization method using block aggregation and integer programming publication-title: J. South. Afr. Inst. Min. Metall. doi: 10.17159/2411-9717/2018/v118n7a4 – volume: 222 start-page: 642 issue: 3 year: 2012 ident: 10.1016/j.resourpol.2018.11.004_bib20 article-title: A diversified Tabu search approach for the open-pit mine production scheduling problem with metal uncertainty publication-title: Eur. J. Oper. Res. doi: 10.1016/j.ejor.2012.05.029 – volume: 38 start-page: 212 issue: 2 year: 2013 ident: 10.1016/j.resourpol.2018.11.004_bib2 article-title: An uncertainty based multi-criteria ranking system for open pit mining cut-off grade strategy selection publication-title: Resour. Policy doi: 10.1016/j.resourpol.2013.01.004 – volume: 38 start-page: 591 issue: 4 year: 2013 ident: 10.1016/j.resourpol.2018.11.004_bib1 article-title: A heuristic approach to stochastic cutoff grade optimization for open pit mining complexes with multiple processing streams publication-title: Resour. Policy doi: 10.1016/j.resourpol.2013.09.008 – volume: 316 year: 2004 ident: 10.1016/j.resourpol.2018.11.004_bib15 article-title: Managing risk and waste mining in long-term production scheduling of open-pit mines publication-title: SME Trans. – volume: 103 year: 1994 ident: 10.1016/j.resourpol.2018.11.004_bib9 article-title: Open-pit design and scheduling by use of genetic algorithms. Transactions of the institution of mining and metallurgy publication-title: Sect. A. Min. Ind. – volume: 120 start-page: 158 issue: 3 year: 2011 ident: 10.1016/j.resourpol.2018.11.004_bib33 article-title: Two-stage clustering algorithm for block aggregation in open pit mines publication-title: Min. Technol. doi: 10.1179/1743286311Y.0000000009 – start-page: 577 year: 2016 ident: 10.1016/j.resourpol.2018.11.004_bib23 article-title: Joint Conditional Simulation of an Iron Ore Deposit Using Minimum or Maximum Autocorrelation Factor Transformation – start-page: 385 year: 2007 ident: 10.1016/j.resourpol.2018.11.004_bib28 article-title: Stochastic optimisation of long-term production scheduling for open pit mines with a new integer programming formulation. orebody modelling and strategic mine planning publication-title: Australas. Inst. Min. Metall., Melb. – ident: 10.1016/j.resourpol.2018.11.004_bib13 – year: 2014 ident: 10.1016/j.resourpol.2018.11.004_bib16 – volume: 93 start-page: 53 issue: 1038 year: 2000 ident: 10.1016/j.resourpol.2018.11.004_bib37 article-title: Mineral resource+ engineering, economic and legal feasibility publication-title: CIM Bull. – volume: 32 start-page: 919 issue: 8 year: 2000 ident: 10.1016/j.resourpol.2018.11.004_bib10 article-title: Geostatistical simulation of regionalized pore-size distributions using min/max autocorrelation factors publication-title: Math. Geol. doi: 10.1023/A:1007570402430 – volume: 27 start-page: 349 issue: 2–3 year: 2003 ident: 10.1016/j.resourpol.2018.11.004_bib7 article-title: An application of branch and cut to open pit mine scheduling publication-title: J. Glob. Optim. doi: 10.1023/A:1024835022186 – ident: 10.1016/j.resourpol.2018.11.004_bib34 – volume: 44 start-page: 449 issue: 4 year: 2012 ident: 10.1016/j.resourpol.2018.11.004_bib6 article-title: Multivariate block-support simulation of the Yandi iron ore deposit, Western Australia publication-title: Math. Geosci. doi: 10.1007/s11004-012-9402-9 – volume: 14 start-page: 361 issue: 2 year: 2013 ident: 10.1016/j.resourpol.2018.11.004_bib29 article-title: Production scheduling with uncertain supply: a new solution to the open pit mining problem publication-title: Optim. Eng. doi: 10.1007/s11081-012-9186-2 – volume: 121 start-page: 20 issue: 1 year: 2012 ident: 10.1016/j.resourpol.2018.11.004_bib18 article-title: Robust, flexible and operational mine design strategies publication-title: Min. Technol. doi: 10.1179/1743286311Y.0000000018 – volume: 116 start-page: 109 issue: 3 year: 2007 ident: 10.1016/j.resourpol.2018.11.004_bib21 article-title: Stochastic optimisation model for open pit mine planning: application and risk analysis at copper deposit publication-title: Min. Technol. doi: 10.1179/174328607X228848
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Snippet	Stochastic integer programming (SIP) has recently been studied to manage the risk caused by geological uncertainty when solving mine planning and production...
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SubjectTerms	Aggregate data Algorithms Case studies Computer simulation Datasets Integer programming Integers Iron and steel making Iron compounds Iron ore production scheduling Iron ores Large-scale optimisation Mathematical programming Mineral deposits Mining Mining industry Open pit mining Optimization Ores Present value Production Production scheduling Risk Risk management Stochastic integer programming TopCone algorithm Uncertainty Variables
Title	A new risk-based optimisation method for the iron ore production scheduling using stochastic integer programming
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