Dig-limits optimization through mixed-integer linear programming in open-pit mines

Abstract

As a type of general layout problems, dig‐limits optimization focuses on generating the ore‐waste boundaries of a bench sector in an open‐pit mining operation. Typically, blast holes are dense; therefore, selective mining units (SMUs) are small, which is not compatible with loading equipment. Loader cannot select ore‐waste boundaries of SMUs because the arm of the excavator is generally longer than SMU sizes. Therefore, clusters of SMUs being compatible with loader movements need to be formed. In this paper, the dig‐limits optimization problem is shown to be NP‐hard and formulated to maximize profit to be obtained from a mining sector such that ore and waste clusters corresponding to mine excavator movements are considered and solved by mixed‐integer linear programming. To see the efficiency of the proposed approach, a case study is conducted on seven sectors of a bench in a gold mine. The results showed that the approach is practical and has potential to increase the value of operation. The resulting average economic value of seven sectors is $129,060. Additionally, optimal design of one bench solved by the model is compared to a manual design of a mining engineer and a deviation of 6.4% has been observed.

Keywords:

• Dig-limits optimization
• short-term mine planning
• dilution/loss management
• mixed-integer linear programming

Acknowledgements

The authors thank the Natural Sciences and Engineering Research Council of Canada (NSERC) for supporting this research (Fund No.: 236482).