Mine water cooperative optimal scheduling based on improved genetic algorithm

This article addresses the issues of unreasonable water scheduling and high costs in coal mine shafts, proposing a hierarchical optimization scheduling strategy. Taking the water quality and quantity of a certain mining area in Inner Mongolia as the research object, it designs the objective function with the highest reuse efficiency and the lowest reuse cost of mine water resources, and establishes the constraint conditions of water quality and quantity for each water-using unit. In response to the problem that traditional genetic algorithms are prone to local optima, an adaptive autobiographical operator is proposed and improved based on Metropolis principle of simulated annealing algorithm. The improved algorithm is applied to the calculation of the scheduling model, and the results show that the recovery cost in the heating season is reduced by 66779.36 CNY/month, a decrease of 10.34%; the recovery cost in the non-heating season is reduced by 61469.28 CNY/month, a decrease of 9.91%. At the same time, the heating season and the non-heating season have reduced by 136.99 h/month and 154.52 h/month respectively, significantly reducing the recovery cost and time. •A mathematical model for a mine water coordinated scheduling system is established based on the classification of mine water in the mining area and multi-objective water supply rules.•An improved genetic simulated annealing algorithm is proposed to optimize the mine scheduling model with complex water constraints and multiple scheduling processes.•To address the premature convergence issue of the genetic algorithm, it is combined with simulated annealing. Adaptive improvements are made to the crossover, mutation, and random perturbation processes, enhancing the algorithm's search capability.