计算机与现代化

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改进蚁群算法在装备保障路径选择中的应用

  

  1. (1.装甲兵工程学院信息工程系,北京100072;2.华中农业大学资源与环境学院,湖北武汉430070)
  • 收稿日期:2015-06-16 出版日期:2015-11-12 发布日期:2015-11-16
  • 作者简介:陈曼青(1968-),女,上海人,装甲兵工程学院信息工程系副教授,硕士生导师,研究方向:计算机应用技术; 武子荣(1991-),男,河北邢台人,硕士研究生,研究方向:计算机应用技术; 崔伟宁(1978-),男,山东青岛人,讲师,研究方向:计算机应用技术; 常婷婷(1990-),女,河北省邢台人,硕士,研究方向:数字图像处理。
  • 基金资助:

Application of Improved Ant Colony Optimization Algorithm in Equipment Support Route Selection

  1. (1. Department of Information Engineering, Academy of Armored Force Engineering, Beijing 100072, China; 2. College of Resources & Environment, Huazhong Agricultural University, Wuhan 430070, China)
  • Received:2015-06-16 Online:2015-11-12 Published:2015-11-16

摘要: 目前,保障单位在进行装备保障的资源调配时很多都是基于人工决策的,根据经验选择路径,形成保障方案,这存在决策不科学、路径不最优、方案不合理等方面的不足。根据上述状况,利用蚁群算法试验不同的参数值,提出最佳解决方案,对资源调配中的路径进行优化选择,改进基本蚁群算法。实验结果表明,利用改进的蚁群算法进行路径优化确实能够减少时延,提高效率。

关键词: 装备保障, 蚁群算法, 资源调配, 路径优化, 算法改进

Abstract: At present, many of supporting units are based on artificial decision when they deployed resources of equipment support. Using the experience, route is chosen and a security scheme is formed. But artificial decision-making is not scientific, the path is not optimal and the scheme is unreasonable. According to the above conditions, this paper uses ant colony algorithm to experiment with different parameter values, and puts forward the best solution, optimizes route selection in the allocation of resources, then improves the basic ant colony algorithm. The experimental comparison results show that the improved ant colony algorithm can reduce the delay and improve the efficiency of the route optimization.

Key words: equipment support, ant colony algorithm, resource allocation, route optimization, algorithm improvement

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