Adaptive simultaneous stochastic optimiz

This study presents an innovative strategic mine planning approach applied to a multi-mine and multi-process gold mining complex, focusing on simultaneous feasible capital investment alternatives and capacity management decisions. The objective was to develop a comprehensive stochastic optimization framework that enables decision-making regarding extraction sequences, stockpiling, processing streams, blending, waste management, and capital investments within a singular mathematical model. Methodologically, the proposed optimization framework accommodates uncertainties by adapting a production schedule based on various potential investment alternatives aimed at enhancing mill throughput, improving blending, or increasing tailings capacity. The analysis encompasses a mining complex comprising two open-pit gold mines alongside externally sourced ore, with an integrated approach managing diverse processing streams and acid consumption for refractory ore blending. Results indicate that the adaptive production scheduling led to a 6.4% increase in Net Present Value (NPV) through autoclave capacity expansion, while a second investment-free strategy resulted in a significant 27.5% NPV improvement. Ultimately, the adaptive simultaneous optimization demonstrates pronounced advantages over the conventional non-branching two-stage stochastic integer programming approach.