Autonomous mining truck cluster scheduling optimization considering terrain characteristics of open-pit mines

Abstract

With the rapid advancement of intelligent mining, the efficient, safe, and coordinated scheduling of autonomous mining truck clusters has become a critical research focus in open-pit operations. This study addresses the challenges posed by complex terrain conditions in open-pit mines by introducing the Scheduling Optimization Model for Autonomous Mining Truck Clusters Considering Terrain Characteristics (SOM-AMTC). The model systematically integrates key terrain features such as road gradients and curve density into the scheduling process. By integrating these factors into the objective function, the model not only optimizes transportation cost and efficiency but also proactively enhances operational safety. To solve the resulting complex multi-objective optimization problem, a novel hybrid algorithm named CNSGA2-PO is proposed, which combines the strengths of the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and the Parrot Optimization Algorithm (PO). This algorithm improves both global exploration and local exploitation under complex constraints through a constraint-handling mechanism, a hierarchical crossover strategy, and a parrot-inspired behavioral mutation mechanism. Experimental results demonstrate that CNSGA2-PO outperforms comparative multi-objective optimization algorithms in terms of solution quality and computational efficiency. In real-world case studies, the proposed SOM-AMTC model achieves an average reduction in transportation cost of 5.16% and an average increase in transportation efficiency of 5.62%, validating the effectiveness of the model. Particularly noteworthy is that the combined application of CNSGA2-PO and SOM-AMTC achieved a 28.5% reduction in cost alongside a 40% improvement in efficiency, significantly amplifying the synergistic advantages of the algorithm and model. This study offers a robust and scalable technical solution for the intelligent scheduling of autonomous truck clusters in complex open-pit mining environments, supporting the goals of low-cost, high-efficiency, and safe smart mining.