Optimal transportation path planning of truck in open-pit mine under dynamic energy consumption

In the production process of open-pit mines, transportation costs account for more than 50% of the total production costs.With the deepening of open-pit mining, truck transportation distances continue to increase, which results in a substantial increase in transportation cost.How to arrange truck transportation routes reasonably is the key for establishing an efficient and economic transportation system.Due to the complex and changeable road environment in open-pit mines, the consumption of trucks in different road conditions will change at any time.Most of the existing studies consider static transportation costs or fuel consumption as the influencing factors for model establishment, so it is difficult to truly reflect the truck's actual transportation conditions.To overcome this problem, this paper analyzes the consumption process of trucks on the haul road, and divides the process of truck transportation into two parts: overcoming haul road resistance and improving ore and rock potential energy.With the comprehensive consideration of five influencing factors including truck weight, truck speed, road grade, road slope and transportation distance, an optimal path planning model for open-pit mines with the goal of minimizing the total transportation power is established.Considering the particularity of the open-pit mines, an improved ant colony algorithm suitable for solving the open-pit mine path problem is proposed based on the basic ant colony algorithm research.The algorithm uses the road section transportation power as a heuristic factor to calculate the transition probability between nodes, and uses an adaptive dynamic factor to adjust the updated process of the population pheromone.In addition, the diversity of the population has been enriched by introducing crossover operators and mutation operators, and the global convergence capability has been improved.Finally, a large open-pit mine in Henan Province is taken as an example for practical application.The results show that the model can finely reflect the actual transportation status of trucks in the haul road environment of mining areas.Among the many influencing factors, road quality and terrain slope are the key factors that affect route selection.