基于混合算法的单配送中心路径优化方法  

The Single Distribution Center Path Optimization Method Based on Hybrid Algorithm

作　　者：闫凯[1] 李爱光[1] 郭健[1] YAN Kai LI Aiguang GUO Jian(Information Engineering University, Zhengzhou 450001, China)

机构地区：[1]信息工程大学,河南郑州450001

出　　处：《测绘科学技术学报》2016年第6期650-653,共4页Journal of Geomatics Science and Technology

摘　　要：遗传算法具有较好的全局收敛性,蚁群算法具有较好的正反馈性,结合二者的优点,对混合算法进行了研究。定义了自适应交叉率和变异率,用遗传算法得到的一组最优解初始化蚁群算法初始状态下信息素的浓度,结合2-opt算法对结果进行优化,得到最优的物流车辆配送方案。实验验证了将混合算法运用于单配送中心车辆路径问题的有效性。Genetic algorithm has good global convergence and ant colony algorithm has good positive feedback. Combining the merits of both, the hybrid algorithm is investigated in this paper. The adaptive crossover rate and mutation rate are defined. According to the genetic algorithm, the initial state of pheromone concentration of ant colony algorithm is initialized. Combined with 2-opt algorithm, the solution is optimized to get the optimal vehicle distribution scheme. The experiments show that the hybrid algorithm is effectively applied to the vehicle routing problem of the single distribution center.

关 键 词：遗传算法 蚁群算法 交叉率 变异率 单配送中心 

分 类 号：P289[天文地球—地图制图学与地理信息工程]