Uncertain Production Scheduling Optimization in Open-Pit Mines and Its Box Robust Counterpart

Document Type : Research Article

Authors

1 Dept. of Mining and Metallurgy, Urmia University of Technology, Iran

2 Dept. of Mining, University of Tehran, Iran

10.29252/anm.2019.9426.1328

Abstract

Summary
The block extraction sequence is among the most challenging and important issues that should be considered through whole mining operations to reach the maximum profit value. Such Open-pit Production Scheduling problems can be solved under either deterministic or non-deterministic states. This study aims to model the problem applying robust counterpart linear optimization which uses the box set based counterpart. Block economic value, as the objective function coefficient and operational capacity, as the constraints coefficients, are considered as uncertainty sources. Exact mathematical modeling using CPLEX solver, is applied to solve the box counterpart. The model, which was solved in deterministic and uncertain conditions, terminated in results with some differences in scheduled plans.
 
Introduction
Open-Pit Production Scheduling (OPPS) concentrates on determining a block extraction sequence in a way that maximizes NPV of the venture under access, mining capacity, and processing capacity constraints and some other criteria such as blending constraints (extracted ore grade). Mathematical formulation of OPPS problem has been modeled by the mixed integer programming (MIP) method. Production scheduling problem solutions are very sensitive to price and cost volatility, ore grade uncertainty, operational capacities and etc. Hence, the scheduling process involves a significant degree of uncertainty. In order to deal with uncertainties, various approaches such as chance-constrained programming, stochastic programing with recourse and RSO, fuzzy programing, robust optimization programing, etc., can be recommended. Robust counterpart optimization techniques are commonly used in engineering optimization problems. Set-induced robust counterpart optimization techniques include interval set, combined interval and ellipsoidal, adjustable box, pure ellipsoidal, pure polyhedral, combined interval, ellipsoidal, and polyhedral set. In this paper, robust counterpart optimization formulation based on the box counterpart is applied to the OPPS problem.
 
Methodology and Approaches
In this paper, convex set-based robust formulation is employed to handle the OPPS problem according to the box counterpart. The source of violations/perturbations in block economic value, mining, and processing capacity are considered and these formulations are implemented for hypothetical copper orebody. Several runs were executed on our data sets consisting of 6250 blocks.
 
Results and Conclusions
It has been concluded that the OPPS solutions are sensitive to block economic value volatility and operational capacities in each period of extraction. Based on robust mathematical framework, which quantitatively measures the sensitivity and analyzes its impact on OPPS problems different schedule plans are obtained for 3D blocks of a hypothetical mine; also, terminated in results with some differences in production scheduled NPV.

Keywords

Main Subjects

Full Text

برنامه‌ریزی زمانی معادن روباز و تعیین ترتیب استخراج بلوک­های درون محدوده‌ی نهایی این معادن معمولاً بر مبنای بیشینه­کردن ارزش فعلی خالص[i] صورت می­گیرد. از سال 1960 تاکنون محققین مختلف برای برنامه­ریزی زمانی استخراج بلوک­های معادن روباز الگوریتم­های مختلفی را با پایه­های ابتکاری و ریاضی، و رویکردهای قطعی و غیرقطعی ارائه کرده‌اند. برخی از مهم‌ترین الگوریتم‌ها و روش­های حل ارائه شده برای برنامه‌ریزی با رویکرد قطعی در مراجع [1-11] ارائه شده است.

 


[i] Net present value (NPV)

References

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Journal of Analytical and Numerical Methods in Mining Engineering
Volume 9, Issue 21
February 2020
Pages 9-19

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History

  • Receive Date: 06 April 2018
  • Revise Date: 12 November 2019
  • Accept Date: 12 November 2019

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