Modelling and optimization technologies have evolved to become an essential tool for optimal mine designs and production schedules, aiming to maximize the economic value to mining assets from their initial assessment and development to closure. New methodologies and algorithms have been developed for complex mining systems that enable the explicit and joint management of orebody, mining, processing and market uncertainties, and show substantial increase in both NPV and metal production. It is evident in all past developments, that the following areas are still main open areas for research: (a) computational complexity of large scale mining optimization problems, (b) endogenous and exogenous uncertainties in the key parameters (geological/mining, financial), and (c) absence of “holistic” optimization of the elements of a mining complex that intelligently adapts to unveiling information.
Our work contributes substantial developments to strategic stochastic mine planning optimization methods, specifically, by integrating and simultaneously optimizing critical elements of mining complexes under uncertainty using our newly develo9pjed, computationally efficient simulation and optimization approaches. Through these contributions, we have changed the mine planning paradigm in several ways, particularly by shifting the focus of the optimizers from the assessment of economic values of extracted materials to the economic values of the products generated and sold to customers, while accounting for major sources of uncertainty (geological/supply). This contribution opens new possibilities to develop and advanced, all-inclusive framework to deal with serval critical issues that could not be previously addressed.
The sustainable development of Earth’s mineral resources is critical for society; it promotes the responsible extraction of raw materials and metals and supports the developmental needs of emerging economies while simultaneously addressing environmental concerns It is widely acknowledged that major uncertainties affect the development and utilization of mineral resources, particularly from supply (geology(, technical (mining, processing and environment), and market (commodity prices, exchange rates) uncertainty.
Within this context, our ongoing research has established a new stochastic modelling and optimization paradigm for mine planning, design, and production scheduling (SMPDS) that has focused on single mines and their production-related aspects. Outcomes include: (a) a new advanced modelling framework for quantifying supply uncertainty, termed high-order spatial simulation as well as multi-point and multi-scale wavelet based geostatistical simulation methods; (b) new complex stochastic mine optimization formulations that include seral other aspects, such as market uncertainties; (c) exploration of serval algorithmic approaches to address the major computational issues in (a) and (b); and lastly, (d) shifting from the established mining black economic-value-driven mine optimization approaches to new stochastic optimization methods that consider only the geological/rock characteristics of these blocks, such as grades, material types and deleterious materials. Our publications from this research outline advances and contributions to science and engineering, as well as the sustainable utilization of mineral
reserves, social responsibility through better financial performance, and technically defendable objective decision-making.
The 5-year research program aims to build upon our previous findings, as well as investigate new research areas that require further developments in understanding, knowledge, and technology. The new research program follows our stochastic SMPDS paradigm in the broader context of “mine production to product development and market delivery”, and aims to explicitly include major environmental elements. The different aspects of a stochastic simulation-optimization include the development of an all-inclusive stochastic supply-meets-demand SMPDS optimization framework and the further development of the high-order geostatistical simulation framework, as needed to quantify the uncertainty of mineral resources considered in SMPDS.
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.
