Math Optimization models that integrate multiple business’ areas

Unifying mine planning through innovation, collaborativity and an integrated view of mining.

Created in Brazil in 2010 by the Operational Research specialist Alexandre Marinho, MiningMath was initially committed to providing consulting services focused on technology for mining. In 2013, Marinho completed his Masters in Mining Engineering, in Canada, producing a research paper on Stochastic Mine Planning. This research composed the theoretical foundation for the development of MiningMath’s first software, Simsched, bringing great technological innovation to mine planning. Thus, the company migrated from consulting to the development of optimization software for open pit mine planning. 


In the following year, multidisciplinary professionals from engineering, geology, computational mathematics and science united skills and efforts, and the company developed a free tool for pit optimization. In 2015, MiningMath launched the first robust version of the commercial product. With a unique optimization methodology on the market, the MiningMath technology is capable of generating diverse solutions useful to build decision trees. The analysis of these trees, in turn, assists in decision-making through risk assessments not constrained by a step-wise approach. The technology was consolidated in the market in 2017, bringing in its essence MiningMath’s trademark: innovation


Since its establishment, MiningMath is dedicated to improving the software and incorporating the most wished solutions of Research & Development investors and mining specialists. The MiningMath technology, as it is currently known, has reached a mature and robust state, with an increasing number of licenses sold worldwide also proving the consistency of the implementation. 

Our workflow is guided by collaboration and partnership, offering unique commercial opportunities for the expansion of businesses and careers in the mining field through the use of the MiningMath technology. We’ve also developed an online platform for the integration of the Community, besides providing free licenses for teaching and disclosing articles developed using MiningMath.

Founding partners Fabrício Ceolin and Alexandre Marinho



The MiningMath Team at EXPOSIBRAM, in 2017

This is just the beginning. Become part of our story!

Leading countries that use and approve the MiningMath technology




Foundation of MiningMath


The SimSched project presents a new algorithm to optimize geometric constraints

2014 to 2017
2014 to 2017

Participation in diverse national and international mining events, leading academic seminars in Colombia and Peru


1st place in Minetech Challenges and Solutions Competition, in Russia, and approval in the first stage of the Finep Startup program


Change in the name of the technology: from SimSched to MiningMath

2020 to date
2020 to date

Constant developments and improvements in the MiningMath technology; launch and improvements of the MiningMath Community; investments in collaboration, partnerships, organizational culture and business solidification.


Reblocking is a method used to decrease the number of blocks in a block model by...

Floating-point numbers

Same scenario, different results? Is it possible to find different results for t...


MiningMath supports and encourages the translation of its knowledge base to mult...

Imperial System

For importing databases, MiningMath uses the metric system exclusively. In case ...

In-Depth MiningMath

This tutorial provides a detailed guidance to the pages in the knowledge base fo...

Theory Validation

MiningMath’s results are only possible due to its proprietary Math Program...

Guaranteed Solutions

Multiple, complex constraints increase the likelihood of not finding or not exis...

MiningMath Uniqueness

MiningMath allows mining managers to improve their strategic analysis through ri...

Time Limit

It is possible to indicate a time limit in hours before running a scenario in th...

Must-Read Articles

In order to take the maximum of MiningMath’s Optimization we recommend this fl...



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