改进蚁群算法在地下矿山运输路径优化的应用  

Application of improved ant colony algorithm in route optimization of underground mine's transportation

作　　者：周科平[1] 翟建波[1] 

机构地区：[1]中南大学资源与安全工程学院、湖南省深部金属矿产开发与灾害控制重点实验室,湖南长沙410083

出　　处：《中南大学学报（自然科学版）》2014年第1期256-261,共6页Journal of Central South University:Science and Technology

基　　金：国家自然科学基金资助项目(51274253);国家自然科学基金重大资助项目(50934006)

摘　　要：为提高地下矿山运输的智能化和自动化管理水平,提出以电机车总运输距离为目标函数,矿石接收点和溜井数目为变量的运输路径优化模型,并利用改进的蚁群算法对模型进行求解,以便得到最佳的运输路径,将该模型应用到国内某矿山井下运输系统,取得比较理想的效果,并进行参数选取的敏感性分析研究。研究结果表明：利用该方法可以快速得到运输系统的最佳配送路径以及最短运输距离为4 415.653 m,并通过试验多次测试得出,各参数的最佳取值范围为蚂蚁数目m为14-23,信息素重要程度因子α为0.5-1.5,启发函数重要程度因子β为1-3,信息素挥发因子ρ为0.05-0.20,迭代次数NC为100-130。In order to improve the intelligent and automated management level of the underground mine＇s transportation, its route optimization model was proposed with the total haul distance of electric locomotive as the objective function, the ore receiving point and the orepass number as variables. Then the improved ant colony algorithm was used for solving the model and getting the best transportation route. The model was applied for a underground mine＇s transport system, and an ideal effect was gotten. Besides, the sensitivity analysis of parameter selection was studied. The results show that the best distribution route of the transport system is quickly gotten by using this method and the shortest distance is 4 415.653 m. In addition, the best values for each parameter are obtained by testing with ant number m being 14-23, pheromone important degree factor a being 0.5-1.5, heuristic function important degree factor β being 1-3, pheromone evaporation factor p being 0.05-0.20, and iteration Nc being 100-130.

关 键 词：改进蚁群算法 地下矿山运输 路径优化 参数选取 

分 类 号：TD529[矿业工程—矿山机电]