MineLib: a library of open pit mining problems

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.

A hybrid method based on linear programming and variable neighborhood descent for scheduling production in open-pit mines

“…Then, we give the %Ave Gap, as defined earlier (the value of the relative gap between the average value Z average of the 10 solutions generated by SH-VND and the optimal value of the linear relaxation). This time, the optimal value of the linear relaxation has not been obtained using CPLEX, but it has been taken from [15]. The authors mention that it has been computed using a modified version of Bienstock-Zuckerberg's algorithm [3].…”

“…The last dataset on which the method proposed in this paper is tested consists of instances from MineLib, a library of publicly available test problem instances proposed by Espinoza et al [15] for three classical types of open pit mining problems. The authors refer to the variant of the open-pit mine production scheduling problem, denoted in this paper by MPSP, as the constrained pit limit problem, and they denote it by CPIT.…”

Logistic Principles Application for Managing the Extraction and Transportation of Solid Minerals

“…Logistic approach application to management of material and accompanying information, financial and service flow has been successfully implemented in various of economy sectors [1][2], including in the area of solid minerals mining [3][4][5][6].…”

Optimizing open-pit block scheduling with exposed ore reserve

“…Finally, constraint [8] declares the nature of the variables involved in the model. The model proposed here (which we name OPBSEO for 'open pit block scheduling with exposed ore reserve') contains #B×T new binary variables with respect to the standard open pit scheduling model (see, for example, CPIT in Espinoza et al (2013)). The model has also #B×(T-1) additional constraints of type [6] and T-1 constraints of type [7].…”

“…The instances considered for this study were obtained from Minelib (Espinoza et al, 2013), a publicly available library of test problem instances for open pit mining problems, some of which correspond to real-world mining projects, making it very interesting for comparison. In our case, we used the Newman1 and Marvin instances described below, because they were more appropriate for our study in terms of the size of the instances (as mentioned before, the resulting problem is quite complex and required long computational times).…”