MiningMath

MiningMath

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One of the unavoidable steps for the next generation of Data Science and Artificial Intelligence technologies applied to mining

The first and only single-step
Mining Optimization Engine

Through Math Optimization models that integrate multiple areas of the business, MiningMath handles all parameters simultaneously and delivers multiple scenarios, accounting for both strategic and tactical aspects.

Math Programming Solver© for 

Windows 64-Bit (x86_64) - 125 MB

SINGLE-STEP SOLUTIONS

FOR ANY STAGE OF YOUR MINING PROBLEM

Super Best Case
Super best case mine optimization
Super Best Case

MiningMath optimizes all periods simultaneously, without the need for revenue factors. It has the potential to find higher NPVs than procedures based on LG/Pseudoflow nested pits, which do not account for processing capacities (gap problems), cutoff policy optimization and discount rate.

Pushbacks
Pushbacks mine optimization
Pushbacks

MiningMath also offers the option of producing Optimized Pushbacks with controlled ore production and operational designs to guide your mine sequencing. Having this broader view in mind, you are already able to begin the scheduling stage or to import .csv and .xlsx results to other mining packages.

Integrated Schedules
Integrated Schedules

When using MiningMath, scheduling and short-term are not followed by a sequence of steps, but are done in a single and optimized process. This process considers all constraints simultaneously. Therefore, an experienced professional can test multiple scenarios by modifying parameters and advance other stages of his/her work, while MiningMath performs the entire optimization.

Main benefits of using MiningMath
  • Find more diverse solutions
  • Add geometric constraints
  • Compare solutions with decision trees
  • Add the short-term design
  • Get results in .csv and .xlsx files

Brochure - PDF - 5.12 MB

FUTURE OVERVIEW

WHAT IS NEXT?

AI and our unique algorithm combining powers!

Autonomous wizards and sensitivity analysis, parallel executions, CAPEX/OPEX, dashboard analysis, and much more!

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Recent news

Bienstock-Zuckerberg Algorithm: Applicability and Limitations

What is the Bienstock-Zuckerber (BZ) algorithm? The Bienstock-Zuckerberg (BZ) algorithm is an approach for solving large-scale, complex scheduling problems in the area of mixed-integer linear programming (MILP), such as those encountered in some direct block scheduling (DBS) formulations. First proposed here and here, the BZ

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Direct Block Scheduling Algorithms

What is Direct Block Scheduling (DBS)? Direct Block Scheduling (DBS) is a modern approach used in the scheduling of mining operations, particularly in open-pit mining. A DBS-based solution operates directly at the block level rather than on larger aggregates like phases or pushbacks, which are

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