Optimisation of rare earth mining using intelligent optimisation algorithms

Rare earth resources, as a strategic key mineral resource for the nation, require efficient and sustainable development. Traditional mining sequence planning methods struggle to comprehensively coordinate the complex interplay of multiple factors. To address these challenges, this study employs a genetic algorithm to efficiently solve the model, aiming to generate an overall optimal or satisfactory mining sequence plan under given constraints. Research validation indicates that the proposed method can more effectively balance the long-term and short-term benefits of a mine's entire lifecycle and better adapt to the spatial complexity of geological conditions in mining areas. Additionally, the study explores key parameter settings for the algorithm and potential improvement strategies to enhance solution performance. This research provides new theoretical support and effective intelligent decision-making tools for the scientific formulation of mining plans for rare earth mines, holding significant theoretical value and practical guidance implications.