• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2011, Vol. 33 ›› Issue (5): 106-111.

• 论文 • 上一篇    下一篇

物流配送车辆路径问题的优化研究

巩固,胡晓婷,卫开夏,郝国生   

  1. (徐州师范大学计算机科学与技术学院,江苏 徐州 221116)
  • 收稿日期:2010-04-16 修回日期:2010-08-13 出版日期:2011-05-25 发布日期:2011-05-25
  • 作者简介:巩固(1976),男,安徽宿州人,硕士生,讲师,研究方向为智能计算和数据挖掘。胡晓婷(1977),女,甘肃秦安人,硕士,讲师,研究方向为密码学和安全协议。卫开夏(1965),男,安徽芜湖人,博士,副教授,研究方向为计算机测控及应用技术。郝国生(1972),男,河北万全人,硕士生,副教授,研究方向为进化计算。
  • 基金资助:

    江苏省高校自然科学基础研究(09KJB120003);徐州师范大学项目基金(08XBL14)

Optimized Performance Research of the Vehicle Routing Problem in Industry Logistics

GONG Gu,HU Xiaoting,WEI Kaixia,HAO Guosheng   

  1. (School of Computer Science and Technology,Xuzhou Normal University,Xuzhou 221116,China)
  • Received:2010-04-16 Revised:2010-08-13 Online:2011-05-25 Published:2011-05-25

摘要:

物流中的车辆路径问题(VRP)是目前组合优化领域的研究热点问题,VRP为NPhard问题。本文在对VRP分析的基础上,建立数学模型,提出了一种适合求解该问题的蚁群遗传融合优化算法。提出的优化算法首先采用蚁群算法在局部阶段产生最好解,然后利用遗传算法的优良基因在全局阶段对优化解进一步优化,以获取最好路径解。实验结果表明,提出的融合算法能高效解决VRP问题,且优化效果比单算法好。

关键词: 车辆路径问题, 融合优化算法, 蚁群算法, 遗传算法, 路径优化

Abstract:

The logistics distribution VRP, which is a typical NPhard problem, is a hot topic in the combinatorial optimization field at present. Based on the analysis about VRP, a mathematical model is built. Aiming at solving the vehicle routing problem, the paper puts forward a combinatorial optimization algorithm of ant colony and genetics in order to gain  optimization. The combinatorial optimization algorithm adopts the ant colony algorithm to gain local optimization solution, and then makes use of the genetic algorithm which reserves some elitist genetic sense units that can steadily pass down to the son generation to optimize the local optimization solution for gaining a  global optimization solution. The experimental results show that the combination optimization algorithm is efficient in solving VRP, and the optimization efficiency of the improved algorithm is superior to that of a single algorithm such as the ant colony algorithm or the genetic algorithm.

Key words: vehicle routing problem;combination optimization algorithm;ant colony algorithm;genetic algorithm;route optimization