Simultaneous stochastic optimization of

This paper addresses the challenges of optimizing complex mining operations, which often face suboptimal solutions due to traditional sequential optimization methods that do not account for uncertainty in key inputs. The objective of the study is to present a stochastic framework that enables simultaneous optimization of various components, including mining, destination, and processing decisions, in a multi-pit, multi-resource open-pit gold mining complex. The methodology involves using stochastic simulations of orebody and commodity prices to inform a comprehensive optimization model. A case study illustrates the significant impact of integrating market uncertainty into the production schedule, allowing for more informed decision-making regarding cut-off grades, material variability, and operational constraints. This integrated approach minimizes prior assumptions and enhances the ability to exploit synergies among extraction sequencing, blending, and processing. The results indicate that the model leads to increased metal production and improved net present values by effectively managing risk through strategic planning. The findings highlight the importance of adopting holistic optimization strategies in the mining sector to maximize economic outcomes while addressing uncertainties.