Abstract: Considering the conditions of the multi-point, scattered distribution, high required score, strict time constraints in the military orienteering, in order to find a path of high score in time and a good standard for the training results, a mixed integer programming model is established, and a hybrid ant colony algorithm(HACA) is proposed based on the deep analysis of route optimization in military orienteering. In the algorithm, the initial solution is gotten by the improved ant colony algorithm(IACA), and the solution is optimized further by selection, crossover and mutation. The feasibility and superiority of the hybrid ant colony algorithm are verified by simulations and the comparison of the algorithm.

Key words: military orienteering, hybrid ant colony algorithm, route optimization, improved genetic algorithm

摘要： 军事定向越野运动中存在点位多、分布散、时间紧、得分要求高等条件,为在规定时间内找到一条得分高的行进线路,找到衡量和分析运动成绩好坏的标准,文中对军事定向越野中的路径优化问题进行了深入分析,建立了混合整数规划模型,设计了一种混合蚁群算法。算法中,首先由改进蚁群算法找到初始解,然后再利用选择、交叉和变异算子进行解的优化,通过仿真实验和算法对比验证了混合蚁群算法的可行性和优越性。

关键词: 军事定向越野, 混合蚁群算法, 路径优化, 改进遗传算法