计算机工程与应用 ›› 2011, Vol. 47 ›› Issue (32): 246-248.

• 工程与应用 • 上一篇    

基于启发式蚁群算法的VRP问题研究

刘晓勇,付 辉   

  1. 广东技术师范学院 计算机科学学院,广州 510665
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2011-11-11 发布日期:2011-11-11

Study on vehicle routing problem based on heuristic ant colony optimization

LIU Xiaoyong,FU Hui   

  1. Department of Computer Science,Guangdong Polytechnic Normal University,Guangzhou 510665,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-11-11 Published:2011-11-11

摘要: 针对蚁群算法求解VRP问题时收敛速度慢,求解质量不高的缺点,把城市和仓库间的距离矩阵和路径节约矩阵信息融入到初始信息素矩阵中作为启发式信息引入到蚁群算法中用于求解有容量限制的车辆路径规划问题(CVRP),在三个基准数据集上的实验研究表明,基于启发式信息的蚁群算法与基本蚁群算法相比能够以较快的速度收敛到较好的解。

关键词: 车辆路径规划问题, 蚁群算法, 启发式方法

Abstract: When Ant Colony Optimization algorithm(ACO) is applied to vehicle routing problem,it always spends much time and has worse solutions.This paper uses ACO based on a heuristic method for vehicle routing problem.This heuristic method combines distance matrix with saving route matrix to assign initial pheromone matrix.Three benchmark datasets are chosen to verify performance of the new algorithm.Experiments show that ant colony optimization based on heuristic information has better solution and spends less time.

Key words: vehicle routing problem, ant colony optimization, heuristic method