In view of the complex nonlinear change of the compressive strength of filling cementation body caused by the chemical compound effect of different proportioning of activator in filling cementitious materials

an intelligent optimization for the mixture ratio of filling cementitious material was proposed. First

uniform design tests were carried out to obtain the compressive strength values of different activator proportions of backfill bodies. Then

improved genetic tree about dynamic adaptive exchange mutation probability and fitness competition exchange mode was used to characterize the high-precision nonlinear complex relationship between the activator material and the compressive strength of the backfill. When computing to the 49th generation

it satisfy the termination rule of the algorithm. The convergence speed was fast and the function precision was high. Finally

the constraint condition was determined and the optimization model of the proportion of activator was established. The global optimization technology of genetic algorithm was used to get the optimal ratio of the activator material to meet the strength requirements of backfill. The intelligent optimization method was utilized to study the ratio of activator for the new filling cementitious material in iron mine. The optimization show that the optimum proportion for the strength of the mine backfill was 2.91% lime

17.39% gypsum

and 79.7% slag powder. Verification test was carried out around the optimum proportion

and results show that the compressive strength of the filling body at 7 d and 28 d reach the maximum when lime was 3%

gypsum was 17%

and slag powder was 80%

which was in accordance with the test results. Compared with 42.5 cement

the whole tailings filling cementing material could be prepared by the activator proportion prepared by the intelligent optimization method

and the cost of cementing material could be reduced by 22%.