| 一种求解高校最短路径的改进的启发式蚁群算法 |
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| 引用本文： | 方昕.一种求解高校最短路径的改进的启发式蚁群算法[J].计算机与数字工程,2012,40(7):16-18. |
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| 作者姓名： | 方昕 |
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| 作者单位： | 安康学院电子与信息工程系 安康725000 |
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| 基金项目： | 安康学院计算机应用技术重点学科项目，陕西省计算机科学与技术研究项目，安康学院计算机科学与技术重点学科项目资助 |
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| 摘 要： | 启发信息是地理信息系统（GIS）中的关键，针对蚁群算法易陷入局部最优的缺陷，提出一种带有启发信息的改进蚁群算法。i亥算法在初始化蚁群时引入启发信息指引蚂蚁快速收敛于全局最优解，为平衡全局与局部搜索能力，也改进状态转移概率算子，从而有效提高算法性能，增加种群多样性。实验以Visual Studi02005中C＋＋编程实现仿真，结果表明此算法不但能有效求解GIS的最短路径，而且改进的算法能快速地收敛且精度高。
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| 关 键 词： | GIS 最短路径 启发信息 改进的蚁群算法 |
Improved Heuristic Ant Colony Algorithm to Solve the Shortest Path among Campus |
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| FANG Xin.Improved Heuristic Ant Colony Algorithm to Solve the Shortest Path among Campus[J].Computer and Digital Engineering,2012,40(7):16-18. |
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| Authors: | FANG Xin |
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| Affiliation: | FANG Xin (Dept.of Electronic and Information Engineering,Ankang University,Ankang 725000) |
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| Abstract: | The heuristic information is the key in the geographic information system(GIS).Ant Colony Algorithm(ACO) easily leads to local optimal solution in solving shortest path problem.To overcome this shortcoming,improved ACO with heuristic information is proposed.The ACO introduces heuristic information to guide ants can fast converge to global optimal solution in the initialization of the ant colony.And,the ACO uses dual population search and improves state transition operator for the balance of global and local search capabilities to effectively improve the performance and increase the diversity.There use c++ programming of Visual Studio 2005.net.The results show that this algorithm can not only effectively solve the shortest path problem of GIS,but also has high convergence precision. |
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| Keywords: | GIS shortest path heuristic information improved ant colony algorithm |
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