consumption, penalize deviations from route flow rates Despite clear benefits from the standpoint of emissions reduction in the presented studies, there is much room to further expand the area of fleet management focused on sustainability. The most prominent shortcoming of the aforementioned methodologies is their lack of focus on energy efficiency specifically. A notable exception is Kazemi Ashtiani et al. (2025). However, here the researchers use a simplified approach to model emission generation and fuel usage. Mesa et al. (2025) present a comprehensive overview of new developments in the field of fuel consumption modelling, including the influence of haul road design and payload variations. Some of the contributions presented therein can be directly included in stochastic optimization frameworks, leading to more costefficient and sustainable hauling. 4. Conclusions This work presents current developments in the field of sustainable stochastic mine planning, focused on three broad domains, namely, waste management, material considerations, and fleet optimization. The majority of the studies address the question of sustainability from the perspective of the long term. multiobjective planning, optimizing the extraction schedule based on the NPV with additional considerations. Major efforts are undertaken to minimize waste generation, with some studies aiming to mitigate AMD, simultaneously decreasing costs and potential for environmental damage. A visible interest of the scientific community can be observed in the inclusion of geometallurgical variables such as grindability into optimization models, increasing integration of the extraction stage with downstream processes. Stochastic fleet optimization models also emerge as a promising development, accounting for fuel consumption and emission targets simultaneously. The increased computational complexity of the proposed solutions is clearly visible and addressed by the researchers through the increased introduction of metaheuristic solving techniques. Along with further development and integration of a greater number of processing streams and destinations, this trend is expected to continue. In the future, major contributions to machine learning combined with stochastic mine planning methods can be expected. However, while examining the trends in stochastic mine planning and design efforts, one key conclusion can be drawn. Namely, more sustainable solutions for mineral extraction can be implemented without compromising the NPV of the project. Given the increased pressure on the raw materials industry, both from the regulators and the general public, this provides the mining companies with reassurance that their efforts towards a greener future should not be seen as a financial burden, but rather an opportunity. ACKNOWLEDGEMENTS This project has received funding from the European Union's Horizon Europe Marie Skłodowska-Curie Actions Doctoral Networks under Grant Agreement No
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