改进蚁群算法在装备保障路径选择中的应用

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。

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

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.