Multi-objective optimization for ore blending schemes in the open-pit phosphate mine using an improved NSGA-II algorithm

Abstract

To tackle the challenges of varying phosphate ore characteristics and significant fluctuations in raw ore grade, research has focused on optimizing ore blending from multiple unloading points. Given the dual demands of mining enterprises for high-quality processed ore and low production costs, two optimization objectives have been set: minimizing total grade deviation and minimizing total energy consumption. Based on actual mine production conditions, a multi-objective optimization model is developed. Since the model involves two objectives and numerous constraints, evolutionary optimization is used to solve the problem. However, traditional Pareto dominance relationships in evolutionary algorithms often result in poor convergence and feasibility issues. To overcome these limitations, a new dominance relationship, termed SDN dominance, termed niching-based strengthened dominance, is designed. This enhanced dominance approach is incorporated into non-dominated sorting genetic algorithm II (NSGA-II), replacing standard Pareto dominance. An improved NSGA-II, designated as SDN-NSGAII, is thus developed. Finally, the proposed model and algorithm are tested in a case study of an open-pit phosphate mine. The results demonstrate the effectiveness of the SDN-NSGAII algorithm, highlighting its ability to stabilize ore grades while reducing energy consumption. These findings demonstrate the practicality of the model in guiding mining enterprises to develop scientific production schemes.

Keywords

Open-pit phosphate mine / Multi-objective / Evolutionary optimization / Ore blending

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