Escape-route planning of underground coal mine based on improved ant algorithm

Abstract

When a mine disaster occurs, to lessen disaster losses and improve survival chances of the trapped miners, good escape routes need to be found and used. Based on the improved ant algorithm, we proposed a new escape-route planning method of underground mines. At first, six factors which influence escape difficulty are evaluated and a weight calculation model is built to form a weighted graph of the underground tunnels. Then an improved ant algorithm is designed and used to find good escape routes. We proposed a tunnel network zoning method to improve the searching efficiency of the ant algorithm. We use max-min ant system method to optimize the meeting strategy of ants and improve the performance of the ant algorithm. In addition, when a small part of the mine tunnel network changes, the system may fix the optimal routes and avoid starting a new processing procedure. Experiments show that the proposed method can find good escape routes efficiently and can be used in the escape-route planning of large and medium underground coal mines. © 2013 Guangwei Yan and Dandan Feng.