COSMO — Stochastic Mine Planning Laboratory

Modelling and optimization techniques have become a standard core aspect of mine design and production scheduling (MDPS) because they maximize the economic value contributed by ore production from a mine and define a technical plan to be followed from a mine’s development to its closure. MDPS optimization is a complex problem to address due to its large scale, the unavailability of a truly optimal net present value (NPV) solution, uncertainty in the key parameters involved (geological/mining, financial) and the absence of a method for global or simultaneous optimization of the individual elements of a mining complex. To take our past research developments to the next level, research efforts focus on developing optimization that integrates uncertainty in a global sense and simultaneously considers all elements of a mining complex.

Founded upon our research outcomes to date, global optimization of mining complexes id based on two complementary elements: (I) A new stochastic combinatorial optimization framework for MDPS that integrates multiple mines, material types, ore/waste processing streams including stockpiles, and generates different product specifications suitable for a diverse group of commodities and mining complexes. (II) New ‘high-order’ spatial mathematical models of uncertainty for multiple material types generating inputs for Point (I), suitable for modeling complex nonlinear, non-Gaussian geologic formations and spatial architectures. Research aims to contribute new methods to the Canadian and global mining industry that aim to change the way problem-solving in the field is approached and impact on: (a) risk management and maximization of return on investment; (b) economic performance and sustainability; (c) enhancement of production and product supply; (d) objective and technically defendable decision-making; and (e) training highly qualified personnel.