Research on scheduling algorithm for unmanned trucks in open-pit coal mines

Aiming at the multi-objective traffic flow allocation and scheduling problem of unmanned trucks in open-pit mines, a traditional multi-objective traffic flow allocation and scheduling model for open-pit mine trucks was established from three aspects: revenue, cost, and ore quality, with the objective functions of minimizing transportation costs, minimizing total queue time of unmanned trucks, and minimizing grade deviation. Combining multi-objective genetic algorithm and decomposition based multi-objective optimization algorithm adaptability and characteristics, a new decomposition based constrained dominance principle NSGA-II (DBCDP-NSGA-II) optimization algorithm based on decomposition constrained dominance was proposed, which combines Pareto dominance and decomposition with constraint dominance. And the algorithm was applied to solve the multi-objective traffic flow allocation and scheduling model of unmanned trucks in open-pit mines. The results showed that the traffic flow allocation and scheduling algorithm reduced the transportation cost in open-pit mining, reduced the queuing time of unmanned trucks, and effectively controlled the fluctuation of grade.