Application Of Multi-objective Traffic Assignment And Scheduling Algorithm For Driverless Truck In Open Pit Mine

With the continuous development of open pit mining,To improve the safety production efficiency of modern open pit mine,the use of driverless trucks instead of traditional trucks as a means of transportation will play an increasingly important role in the production of open pit mines.Under the background of driverless trucks,open-pit mine driverless truck flow allocation scheduling is the core content of the new open-pit mine driverless truck scheduling.Reasonable driverless truck distribution scheduling will greatly improve the efficiency of intelligent mining.To promote the development of new open-pit mines towards unmanned,intelligent,refined,and efficient development,the thesis focuses on the problem of multi-objective traffic assignment and scheduling of driverless trucks in open-pit mines:(1)This paper summarizes the theoretical research and optimization research of mine truck flow allocation and scheduling models at home and abroad,summarizes the problem of traditional artificial driving flow allocation and scheduling,and compares the similarities and differences between the new open-pit mine unmanned truck flow allocation scheduling and the traditional manual driving truck scheduling problem.Analyze and make a theoretical basis for establishing a multi-objective driverless trucks flow allocation and scheduling model.At the same time,the basic concepts of multi-objective optimization and the multi-objective optimization algorithm are summarized,and it is the theoretical foundation for solving the multi-objective traffic flow scheduling model of driverless trucks.(2)According to the current research literature,the demand for truck flow allocation and scheduling in open-pit mines mainly comes from three aspects: revenue,cost and ore quality.The minimum transportation cost,the minimum total queue time ofunmanned trucks,and the minimum grade deviation are established.The objective function of the traditional open-pit mine truck multi-objective vehicle flow dispatching model.By comparing with the traditional truck flow distribution and scheduling model,a multi-objective truck flow distribution and scheduling model of open pit mine driverless truck is established under the background of driverless truck,which takes the minimum transportation cost,the minimum total queuing time of driverless truck and the minimum grade deviation as the objective function.(3)According to the characteristics of the multi-objective vehicle flow distribution and scheduling model of the open pit mine driverless truck,combined with the adaptability and characteristics of the multi-objective genetic algorithm and the multi-objective optimization algorithm based on decomposition,a new NSGA-II optimization algorithm(DBCDP-NSGA-II)based on the combination of Pareto domination,decomposition and constraint domination is proposed.The algorithm is used to solve the multi-objective vehicle flow assignment and scheduling model of open pit mine driverless truck.Compared with C-NSGA-II and C-MOEA/D algorithm,DBCDP-NSGA-II has the best solution in three objective functions.In addition,the algorithm includes multiple Pareto optimal solutions and multiple driverless truck flow allocation scheduling plans,which can meet the different production needs of the mine and provide a variety of options for the production managers of the open pit mine.(4)The open-pit mine driverless truck multi-objective vehicle flow allocation and scheduling algorithm and solution algorithm proposed in this study are used in the unmanned truck flow allocation and scheduling management of an open-pit mine intelligent mining area.Select the relevant data of a certain shift of a truck in the open-pit mine intelligent mining area,the result is the pareto optimal solution set,showing the scheduling plan of 20 unmanned trucks,the schedule of No.1 unmanned truck and Gantt in a shift Figures and other results show that the vehicle flow allocation scheduling algorithm reduces the transportation cost in open pit mining,reduces the queuing time of unmanned trucks,and effectively controls the grade fluctuations.