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Mine Planning Above and Below Ground: Generating a Set of Pareto-Optimal Schedules Considering Risk and Return

  • Candace A. YanoEmail author
  • Carson McFadden
Chapter
  • 1.8k Downloads
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 200)

Abstract

Recent years have seen increasing efforts to incorporate risk and uncertainty into optimal and heuristic methods for mine planning and scheduling. The recent volatility in the prices of metals and minerals has provided further impetus for developing new methods that facilitate integrated optimization and risk analysis in mining. We consider a long-term problem of determining a plan for above- and underground mining, allowing for different ways in which the material can be extracted, such as choice of cutoff grade and mining speed. We develop a methodology based on a longest-path network framework that allows us to identify the mining plans that produce the k highest values of expected profit, where k can be chosen by the decision-maker. We couple this with a methodology for evaluating each of these plans with respect to various measures of risk, such as variance, probability of achieving a profit target, or conditional value-at-risk. The framework is easily extendible to other risk measures. The methodology provides a means to construct a set of Pareto-optimal solutions with expected profit and the selected risk measure as the two performance metrics. We illustrate our approach using a simple example in which the risk measure is value-at-risk (VaR).

Keywords

Surface mining Underground mining Planning and scheduling Longest path network Risk Value-at-risk 

Notes

Acknowledgement

This research was undertaken while the first author was a graduate student at the University of California, Berkeley. The first author gratefully acknowledges support from a fellowship from the National Sciences and Engineering Research Council of Canada.

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Haas School of Business and IEOR DepartmentThe University of California - BerkeleyBerkeleyUSA
  2. 2.Watarah AdvisorsTorontoCanada

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