A dynamic combination algorithm based scenario construction theory for mine water-inrush accident multi-objective optimization

Abstract

Mine safety is a crucial aspect of national infrastructure. In recent years, there have been frequent mine safety accidents in China, and the proportion of mine water-inrush accidents (MWAs) is high among them. It causes significant challenges for governments and mine managers. The emergency response of MWAs is a multi-scale expert decision-making system that involves considerable cost, time, and energy consumption. The Mine Accidents Central Control Office is constituted of mine managers and government officials, and it lacks scientific validity in analyzing the risk correlation only based on sensory-historical experience. It can lead to deviations in emergency response capability and cause unnecessary waste of costs, time, and energy. This study introduces scenario construction theory and multi-attribute dynamic combination algorithms to address this systemic challenges based on the data-driven model. Firstly, the dataset is structured by the induction method based on historical MWAs from 2003 to 2023 in China, and it is divided into nine accident attributes and three calculated categories. Secondly, the scenario parameters are selected with bottom-line thinking and correlation analysis of accident attributes. Thirdly, the scenario queue model and scenario disposal model are constructed based on the scenario construction theory with the dynamic combination algorithm; a systemic mathematical model is established to optimize the multi-objective (cost, time, and energy consumption) in emergency response. Finally, a real metal mine is selected for model simulation, based on data results to analyze algorithm variable reflected handle measure. This study provides a novel approach and scientific reference to improve emergency plans in mine safety management. It enhances the effectiveness and timeliness of emergency response in the MWAs.