奖惩机制蚁群算法在煤矿运输路径优化中的应用研究  

Research on application of ant colony algorithm with incentive mechanism to routing of colliery transport

作　　者：赵焕平[1] 张红红[2] 薛党勤[1,3] 

机构地区：[1]南阳理工学院,河南南阳473004 [2]河南牧业经济学院(英才校区)计算机应用系,河南郑州450044 [3]中国农业大学,北京100083

出　　处：《矿山机械》2014年第2期101-104,共4页Mining & Processing Equipment

基　　金：国家自然科学基金资助项目(10771091);国家高科技发展计划(863计划)(2012AA10A503)

摘　　要：在煤矿运输路径优化中,由于传统蚁群算法存在运行时间长和收敛速度慢等缺点,为此笔者通过引入奖惩机制对算法路径的构造规则进行重新设定,对此算法进行了改进,并改进了算法的信息素更新策略,克服了传统蚁群算法的缺陷。仿真结果验证了改进蚁群算法解决煤矿运输路径优化问题的高效性和可行性。In view of the shortcomings of traditional ant colony algorithm such as long operation duration and slow convergence speed during routing of colliery transport, the paper improved the algorithm, and introduced incentive mechanism to reset the constitution rule of the algorithm routes. It also improved the pheromone updating strategy of the algorithm, and overcame the shortcomings of the traditional ant colony algorithm. Simulation results showed that the improved ant colony algorithm was efficient and feasible in routing of colliery transport.

关 键 词：煤矿运输 路径优化 蚁群算法 奖惩机制 

分 类 号：TD56[矿业工程—矿山机电] TP18[自动化与计算机技术—控制理论与控制工程]