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.
Optimization techniques are a core aspect of mine design and production scheduling (MDPS) because they maximize the economic value generated by the production of ore and define a technical plan to be followed from the development of the mine to its closure. MDPS optimization is a complex problem to address due to its large scale, 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. Founded upon our research outcomes to date and the desire of New Millennium Iron Corporation (our industry partner), global optimization of open pit iron ore mining complexes will be addressed through development of a new stochastic optimization framework. This general MDPS framework integrate multiple mines, multiple processing streams, blending stockpiles and waste dumps, while also aiming to meet quality specifications, minimize environmental impact, and minimize transportation costs required for iron ore deposits in Quebec’s North. Simultaneously optimizing all aspects of a mining complex leads to mine designs that not only minimize risk related to environmental impact and rehabilitation, but have previously demonstrated increase of economic value, reserves and life-of-mine forecasts, thus contributing to the sustainable development of non-renewable resources. The research undertaken capitalizes on outcomes from related research at both McGill University and École Polytechnique de Montréal and supports the collaboration between these institutions as well as GERAD research center, where the research is based.
The sustainable development and utilization of mineral resources and reserves ensures the continued supply of raw materials, metals and energy we rely upon. Sustainable development is a critical global problem, particularly given the fast growth and demand of emerging economies and increasing environmental concerns. Several sources of uncertainty impact sustainable mineral resource development: technical, financial, and environmental. Technical and economic uncertainties include the ability of orebodies to supply raw materials, operational mining uncertainties, fluctuating market demand for raw materials and related commodity prices. Based upon our research and learning to date, a new five year research program has commenced to explore and further develop our new stochastic mine and production scheduling paradigm, through: new computationally efficient stochastic optimization methods, new high-order stochastic models, and risk-based financial models. This will include expanding the field of research, addressing new problems encountered in our past research, full-field testing of new methods, and increasing our understanding of the new stochastic framework and related technologies.