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Author Espinoza, D.; Goycoolea, M.; Moreno, E.; Newman, A.
Title MineLib: a library of open pit mining problems Type
Year 2013 Publication Annals Of Operations Research Abbreviated Journal Ann. Oper. Res.
Volume 206 Issue 1 Pages 93-114
Keywords Mine scheduling; Mine planning; Open pit production scheduling; Surface mine production scheduling; Problem libraries; Open pit mining library
Abstract Similar to the mixed-integer programming library (MIPLIB), we present a library of publicly available test problem instances for three classical types of open pit mining problems: the ultimate pit limit problem and two variants of open pit production scheduling problems. The ultimate pit limit problem determines a set of notional three-dimensional blocks containing ore and/or waste material to extract to maximize value subject to geospatial precedence constraints. Open pit production scheduling problems seek to determine when, if ever, a block is extracted from an open pit mine. A typical objective is to maximize the net present value of the extracted ore; constraints include precedence and upper bounds on operational resource usage. Extensions of this problem can include (i) lower bounds on operational resource usage, (ii) the determination of whether a block is sent to a waste dump, i.e., discarded, or to a processing plant, i.e., to a facility that derives salable mineral from the block, (iii) average grade constraints at the processing plant, and (iv) inventories of extracted but unprocessed material. Although open pit mining problems have appeared in academic literature dating back to the 1960s, no standard representations exist, and there are no commonly available corresponding data sets. We describe some representative open pit mining problems, briefly mention related literature, and provide a library consisting of mathematical models and sets of instances, available on the Internet. We conclude with directions for use of this newly established mining library. The library serves not only as a suggestion of standard expressions of and available data for open pit mining problems, but also as encouragement for the development of increasingly sophisticated algorithms.
Address [Espinoza, Daniel] Univ Chile, Dept Ind Engn, Santiago Ctr, Santiago, Chile, Email: daespino@dii.uchile.cl;
Corporate Author Thesis
Publisher Springer Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0254-5330 ISBN Medium
Area Expedition Conference
Notes WOS:000320694000006 Approved
Call Number UAI @ eduardo.moreno @ Serial 290
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Author Letelier, O.R.; Espinoza, D.; Goycoolea, M.; Moreno, E.; Munoz, G.
Title Production Scheduling for Strategic Open Pit Mine Planning: A Mixed-Integer Programming Approach Type
Year 2020 Publication Operations Research Abbreviated Journal Oper. Res.
Volume 68 Issue 5 Pages 1425-1444
Keywords open pit mining; production scheduling; column generation; heuristics; cutting planes; integer programming applications
Abstract Given a discretized representation of an ore body known as a block model, the open pit mining production scheduling problem that we consider consists of defining which blocks to extract, when to extract them, and how or whether to process them, in such a way as to comply with operational constraints and maximize net present value. Although it has been established that this problem can be modeled with mixed-integer programming, the number of blocks used to represent real-world mines (millions) has made solving large instances nearly impossible in practice. In this article, we introduce a new methodology for tackling this problem and conduct computational tests using real problem sets ranging in size from 20,000 to 5,000,000 blocks and spanning 20 to 50 time periods. We consider both direct block scheduling and bench-phase scheduling problems, with capacity, blending, and minimum production constraints. Using new preprocessing and cutting planes techniques, we are able to reduce the linear programming relaxation value by up to 33%, depending on the instance. Then, using new heuristics, we are able to compute feasible solutions with an average gap of 1.52% relative to the previously computed bound. Moreover, after four hours of running a customized branch-and-bound algorithm on the problems with larger gaps, we are able to further reduce the average from 1.52% to 0.71%.
Address [Rivera Letelier, Orlando] Univ Adolfo Ibanez, Doctoral Program Ind Engn & Operat Res, Santiago 7941169, Chile, Email: orlando.rivera@uai.cl;
Corporate Author Thesis
Publisher Informs Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0030-364x ISBN Medium
Area Expedition Conference
Notes WOS:000574409100008 Approved
Call Number UAI @ alexi.delcanto @ Serial 1250
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Author Moreno, E.; Rezakhah, M.; Newman, A.; Ferreira, F.
Title Linear models for stockpiling in open-pit mine production scheduling problems Type
Year 2017 Publication European Journal Of Operational Research Abbreviated Journal Eur. J. Oper. Res.
Volume 260 Issue 1 Pages 212-221
Keywords OR in natural resources; Stockpiling; Linear and integer programming; Mine planning; Open pit mining
Abstract The open pit mine production scheduling (OPMPS) problem seeks to determine when, if ever, to extract each notional, three-dimensional block of ore and/or waste in a deposit and what to do with each, e.g., send it to a particular processing plant or to the waste dump. This scheduling model maximizes net present value subject to spatial precedence constraints, and resource capacities. Certain mines use stockpiles for blending different grades of extracted material, storing excess until processing capacity is available, or keeping low-grade ore for possible future processing. Common models assume that material in these stockpiles, or “buckets,” is theoretically immediately mixed and becomes homogeneous. We consider stockpiles as part of our open pit mine scheduling strategy, propose multiple models to solve the OPMPS problem, and compare the solution quality and tractability of these linear-integer and nonlinear-integer models. Numerical experiments show that our proposed models are tractable, and correspond to instances which can be solved in a few seconds up to a few minutes in contrast to previous nonlinear models that fail to solve. (C) 2016 Elsevier B.V. All rights reserved.
Address [Moreno, Eduardo; Ferreira, Felipe] Univ Adolfo Ibanez, Fac Sci & Engn, Avda Diagonal Torres 2700, Santiago, Chile, Email: eduardo.moreno@uai.cl;
Corporate Author Thesis
Publisher Elsevier Science Bv Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0377-2217 ISBN Medium
Area Expedition Conference
Notes WOS:000396952000018 Approved
Call Number UAI @ eduardo.moreno @ Serial 715
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Author Rezakhah, M.; Moreno, E.; Newman, A.
Title Practical performance of an open pit mine scheduling model considering blending and stockpiling Type
Year 2020 Publication Computers & Operations Research Abbreviated Journal Comput. Oper. Res.
Volume 115 Issue Pages 12 pp
Keywords Stockpiling; Linear and integer programming; Mine planning; Open pit mining; Software
Abstract Open pit mine production scheduling (OPMPS) is a decision problem which seeks to maximize net present value (NPV) by determining the extraction time of each block of ore and/or waste in a deposit and the destination to which this block is sent, e.g., a processing plant or waste dump. Spatial precedence constraints are imposed, as are resource capacities. Stockpiles can be used to maintain low-grade ore for future processing, to store extracted material until processing capacity is available, and/or to blend material based on single or multiple block characteristics (i.e., metal grade and/or contaminant). We adapt an existing integer-linear program to an operational polymetallic (gold and copper) open pit mine, in which the stockpile is used to blend materials based on multiple block characteristics, and call it ((P) over cap (la)). We observe that the linear programming relaxation of our objective function is unimodal for different grade combinations (metals and contaminants) in the stockpile, which allows us to search systematically for an optimal grade combination while exploiting the linear structure of our optimization model. We compare the schedule of ((P) over cap (la)) with that produced by (P-ns) which does not consider stockpiling, and with ((P) over tilde (la)), which controls only the metal content in the stockpile and ignores the contaminant level at the mill and in the stockpile. Our proposed solution technique provides schedules for large instances in a few seconds up to a few minutes with significantly different stockpiling and material flow strategies depending on the model. We show that our model improves the NPV of the project while satisfying operational constraints. (C) 2019 Elsevier Ltd. All rights reserved.
Address [Rezakhah, Mojtaba] Tarbiat Modares Univ, Engn Dept, POB 14115411, Tehran, Iran, Email: m.rezakhah@modares.ac.ir;
Corporate Author Thesis
Publisher Pergamon-Elsevier Science Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0305-0548 ISBN Medium
Area Expedition Conference
Notes WOS:000514218600009 Approved
Call Number UAI @ eduardo.moreno @ Serial 1161
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