摘要
针对标准蚁群算法易陷入早熟收敛的缺陷且为求解高校路网问题,提出一种求解高校路网的改进蚁群算法。该算法引入了一定比例的逆向蚁群与自平衡搜索策略,以平衡两种群求解并判定算法是否陷入局部最优,采用改进的状态转移概率算子引导蚁群转移,有效提高算法性能,增加种群多样性。实验以Visual Studio2005中C++编程实现仿真,结果表明此算法不但能有效求解高校路网最短路径,而且改进的算法收敛精度高,有效克服了早熟收敛问题。
Standard ant colony algorithm （ ACO） easily leads to premature convergence in solving university path problem. To overcome this shortcoming,improved ACO is proposed. The ACO introduces a certain percentage reverse ant colony and self-balancing strategy to judge whether ACO starts to a local optimum solution. And a modified state transition operator will guide the ant colony transfer to effec tively improve the performance and increase the diversity. There use C＋＋ programming of Visual Studio2005. net. The results show that this algorithm can not only effectively solve the university shortest path problem, but also has high convergence precision and overcomes premature convergence effectively.
出处
《计算机技术与发展》
2012年第12期142-145,共4页
Computer Technology and Development
基金
陕西省科学与技术研究计划项目(2010JM3020)
安康学院计算机应用技术重点学科项目(AKXYZDXK 003)
安康学院计算机科学与技术重点学科项目
关键词
高校路网
逆向蚁群
最短路径
改进蚁群算法
university path
reverse ant colony
shortest path
improved ant colony algorithm
