【摘要】 针对车辆路径搜索对其计算质量和效率要求较高问题,且原始蚁群算法和标准粒子群算法均存在局部优先解、停滞以及收敛速度较慢等缺陷,提出一种融合改进的蚁群和粒子群路径搜索算法。在融合算法前期提高粒子群算法收敛速度,利用其进行粗搜索,后期利用改进的蚁群算法进行细搜索。通过仿真分析表明,融合后的改进算法在路径规划和计算效率上均有较大提升。更多还原

【Abstract】 The ant colony and particle swarm optimization have the disadvantages of local preferred solution,stagnation and low convergence speed. A fusion of improved ant colony and particle swarm algorithm is proposed to meet the high quality and efficiency requirements of vehicle routing search.,use the coarse search is used in the early stage,and the improved ant colony algorithm for the following fine search. Simulation shows that the improved algorithm significant improves the efficiency of path planning and calculation.更多还原