Mine water cooperative optimal scheduling based on improved genetic algorithm

Yang Liu; Zihang Zhang; Dongxu Zhu; Lei Bo; Shangqing Yang; Yuangan Yue; Yiying Wang

doi:10.1016/j.heliyon.2024.e27289

Mine water cooperative optimal scheduling based on improved genetic algorithm

Heliyon. 2024 Mar 1;10(6):e27289. doi: 10.1016/j.heliyon.2024.e27289. eCollection 2024 Mar 30.

Authors

Yang Liu¹, Zihang Zhang¹, Dongxu Zhu², Lei Bo¹, Shangqing Yang¹, Yuangan Yue¹, Yiying Wang³

Affiliations

¹ School of Mechanical Electronic & Information Engineering, China University of Mining and Technology (Beijing), Beijing, 100083, China.
² China Academy of Launch Vehicle Technology, Beijing, 100086, China.
³ School of Mechanical and Equipment Engineering, Hebei University of Engineering, Handan, Hebei, 056038, China.

Abstract

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.

Keywords: Cooperative scheduling; Improved genetic algorithm; Mine water; Reuse cost.