文章摘要
基于空间聚类和蚁群算法的车辆路径问题的研究
Research and Practice of VRP Based on the Improved K-means and Ant Colony Algorithm
  
DOI:10.3969/j.issn.1671-5322.2009.04.013
中文关键词: 车辆路径问题  蚁群算法  聚类分析  改进K-means算法
英文关键词: VRP  Ant Colony Algorithm  Clustering Analysis  improved K-means
基金项目:
作者单位
朱锦新 盐城工学院实验教学部江苏盐城224051 
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中文摘要:
      针对蚁群算法在解决车辆路径问题(VRP)上易陷入局部最优解的缺陷,首先利用加权K-means算法对客户进行区域划分,再利用蚁群算法对每个区域进行求解,实验结果表明方法具有良好的性能.
英文摘要:
      A study is made on VRP.To avoid long-time searching、precocity and stagnation and tendency to local optimization of traditional ant colony algorithm.First,improved K-means is applied to divide regions of customs,ant colony algorithm is applied to solve the problem in each region.Experiments indicate that the proposed method has good performance.
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