混合蚁群算法在车辆路径问题中的应用

蚁群算法在求解车辆路径问题过程中存在搜索时间长、易于陷入局部最优解的问题。为此，设计并实现一种混合蚁群算法。引入变异算子增强算法的全局搜索能力，采用2-opt法优化阶段最优解的子路径。通过对信息素的挥发因子进行动态调整，从而有效控制信息量的变化速度。实例仿真结果表明，该算法具有较好的求解效率和寻优效果。

Application of Hybrid Ant Colony Algorithm in Vehicle Routing Problem

Ant Colony Algorithm（ACA） has some short-comings such as its slow computing speed, and it is easy to fall in a local optimal. Based on the idea of ACA, a hybrid optimization algorithm for solving Vehicle Routing Problem（VRP） is proposed. The algorithm expands the scope of solution space and improves the global ability of the algorithm by importing mutation operator, optimizes the stage optimal solution further by combining 2-opt, and controls the rate of change in pheromone by adjusting configuration of parameters dynamically. Example simulation results show that this algorithm can get optimal resolution of VRP effectively and quickly.