Optimization And Simulation Of Truck-shovel Allocation In Large-scale Metal Open-pit Mine Based On Match Factor

The investment and operating costs of open-pit mines equipment gradually step up with the expansion of the mine scale.The devotion of equipment in open pit production accounts for about 80% of the input of mine.When the scale of open-pit mines is expanded,reducing equipment investment costs is one of the important issues.The transportation costs in production accounts for more than 60% of the total operation cost of the mine,and the transportation costing mainly comes from trucks.During operation,if the truck-shovel allocation is not properly,there will be truck queue and shovel idling,so it is necessary to optimize the truck-shovel allocation.The match factor is one of the most important criteria to measure the efficiency of the shovel-truck operation system.In this paper,the following research has been carried out for the optimization of shoveltruck allocation in open-pit mine:(1)The related research and theoretical summary of the optimization of truck-shovel allocation in large-scale metal open-pit mines.Firstly,the relevant research methods of open-pit truck-shovel allocation optimization model at home and abroad are summarized,the concepts and theories of multi-objective and single-objective truck fleet optimization in open-pit mines and the desirability of installing multi-objective truck-shovel allocation optimization model are systematically reviewed.The traditional solution method,the basic meaning and common methods of simulation experiment and intelligent optimization algorithm are summarized.It makes a theoretical foundation for the next optimization model of surface mine truck shovel configuration based on match factor.(2)The optimization model of truck-shovel allocation based on match factor in largescale metal open-pit mines.According to the physical circumstance of shovel-truck production and transportation,the goal is to minimize the deviation of match factor and transportation costs and to maximize the throughput of shovel.In order to control the costing of equipment in open-pit mines,the production requirements and transportation of loading and dumping point are considered comprehensively.At the same time,the truck operation cost and the truck fleets size are reduced,and the excellent management of the transportation is realized.(3)The model of truck-shovel allocation in large-scale metal open-pit mines is solved.Based on the MPIO algorithm,the special crowding distance calculation based on clustering method and the population search strategy are further proposed.The CSMPIO algorithm is improved to solve the model of truck-shovel allocation in open-pit mines.The CSMPIO algorithm is used to solve the special test function with multiconstraints and multi-objects,and the effectiveness of the algorithm is verified by simulation examples.(4)The simulation and application optimization model for truck-shovel allocation in large-scale mental open-pit mines.Based on the experiment of an open-pit mine,the data needed to solve the problem are obtained by using the open-pit intelligent mining production management platform,and the practical simulation and application is carried out.Results show that the optimization model and algorithm can better satisfied the needs of the throughput of the mine.The availability of the optimization model can be verified by Flex Sim simulation software,and further optimization can be made based on the results of the model solution.Comparing the results before and after optimization,it can be seen that the simulation experiment has effectively improved the efficiency and increased the ore throughput.The research results of the thesis provide a solution for the optimization of shoveltruck allocation in the design stage of large-scale metal open-pit mine,to a certain extent,the cost of investment in mining equipment is reduced and economic benefits are increased.