Theory and method of genetic-neural optimizing cut-off grade and grade of crude ore

摘要

Cut-off grade for ore drawing is a kind of technological method used to control the process of drawing in sublevel caving with no sill pillar. The cut-off grade for ore drawing means the grade of ore in the last time (current time) of ore drawing. Grade of crude ore is the grade of ore entering the milling workshop after ore mixing. Cut-off grade and grade of crude ore are key parameters of production and management in mine system. Genetic algorithm and neural networks nesting method are used in this research to simulate the highly complexity and highly non-linear relationship between variables in mining system, to optimize the cut-off grade and grade of crude ore. The idea is detailed as follows. Cut-off grade and grade of crude ore are joined as chromosome of population for evolution computation; Self-adaptive neural network is used to obtain the local connection between the revenue (fitness function) and chromosome; Genetic algorithm is performed to search the optimal cut-off grade and grade of crude ore globally. The inner layer of nesting is neural networks, which is used to compute loss rate, amount of tailing ore and total cost; the outer layer is evolutionary computation, which is used to get the revenue. The inner layer carries out local approximation, and the outer carries out global search. These two layers carry out the optimization of cut-off grade and grade of crude ore jointly. Take Daye Iron Mine as an example, and the result shows that, the present scheme (cut-off grade is 18%, grade of crude ore is 41–43%) should be improved. During the period of August to November in the year 2007, the optimal cut-off grade is 15.8%, and optimal grade of crude ore is 43.7762–44.1387%, the optimized scheme can improve the present value by 9.01–9.44 million yuan.