基于改进蚁群算法的多约束供应保障网络路径优化

Path Optimization for Multi-Constrained Supply Support Network Based on Improved Ant Colony Algorithm

针对网络优化领域中的多约束网络路径优化问题,以战时供应保障路径优化问题为研究对象,建立一种保障代价最小的路径优化模型。分析保障路径优化中存在多约束限制问题的特点,在基本蚁群算法的基础上引入蚂蚁相遇策略,融合了多约束条件对保障路径优化的影响,通过正、逆反馈同时作用,对信息素更新策略进行改进,并对搜索最优保障路径实例的仿真。仿真结果显示:改进蚁群算法平均执行时间较基本蚁群算法提高了40.1%,说明改进的蚁群算法能在更短的时间内找到最优解,而且在避免陷入局部最优解方面具有更好的效果。

Taking the problem of supply support path optimization in wartime as the research object and aiming at thecharacteristics of multi-constraint limited problem in support path optimization, the optimization model of support path with supply minimum cost was established. Based on general ant colony algorithm, ant encounter strategy is introduced into this algorithm which the positive and negative feedback simultaneously, and pheromone updating policy is improved. The simulation result shows that the improved ant colony algorithm the average execution time increase 40.1% than the basic ant colony algorithm. The new algorithm can find the optimal solution in the shortest time, and it is effective on reducing the possibility of falling in local optimum.