[1]申艳光,张玲玉,刘永红.基于混合遗传算法的物流路径优化方法研究[J].计算机技术与发展,2018,28(03):192-196.[doi:10．3969/j．issn．1673－629X．2018．03．041]
　SHEN Yan-guang,ZHANG Ling-yu,LIU Yong-hong.Study on Optimizing of Physical Ｒouting Method Based on Hybrid Genetic Algorithm[J].,2018,28(03):192-196.[doi:10．3969/j．issn．1673－629X．2018．03．041]
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基于混合遗传算法的物流路径优化方法研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
28
期数:
2018年03期
页码:
192-196
栏目:
应用开发研究
出版日期:
2018-03-10

文章信息/Info

Title:
Study on Optimizing of Physical Ｒouting Method Based on Hybrid Genetic Algorithm
文章编号:
1673－629X(2018)03－0192－05
作者:
申艳光1; 张玲玉1; 刘永红2
1.河北工程大学 信息与电气工程学院，河北 邯郸 056038;
2.中电建建筑集团有限公司，北京 100000
Author(s):
SHEN Yan-guang1 ; ZHANG Ling-yu1 ; LIU Yong-hong2
1．School of Information ＆ Electrical Engineering，Hebei University of Engineering，Handan 056038，China;
2．Electric Construction Group Co．，Ltd．，Beijing 100000，China
关键词:
物流配送; 路径优化; 改进遗传算法; K－means 算法; 混合遗传算法
Keywords:
logistics distribution; route optimization; improved genetic algorithm; K－means; hybrid genetic algorithm
分类号:
TP301.6
DOI:
10．3969/j．issn．1673－629X．2018．03．041
文献标志码:
A
摘要:
从传统的遗传算法机制出发，针对传统遗传算法在解决物流配送路径优化问题中存在早熟和局部搜索能力不足的缺点，提出一种通过聚类分析中 K－means 算法与改进遗传算法相结合的混合遗传算法。其中，选择操作采用精英保留模型的锦标赛选择策略，交叉操作采用双切点交叉，变异算子引入 k－ 交换变异操作保证个体逐代进化。通过选择、交叉和变异操作，实现目标函数的最小化，大大缩减了车辆行驶距离，优化了配送路线，并根据数学模型利用实验数据进行仿真实验，结果表明混合遗传算法相对于原有的遗传算法提高了全局寻优能力和算法的收敛速度。
Abstract:
By analyzing the optimization scheme of traditional genetic algorithm，according to the precocious and insufficient ability of the genetic algorithm in solving the optimization of logistics distribution routing problems of local search，we propose a hybrid genetic algorithm combined with K－means algorithm and improved genetic algorithm．In this algorithm，selection operation adopts the championship selection strategy of elitist model of tournament，crossover operation with double－cut point crossover，and mutation operator introduces the k－exchange mutation operation to guarantee the individual evolution by generation．By selection，crossover and mutation operations，the objective function is minimized，the vehicle distance is reduced greatly，and the distribution route is optimized．The experiments are carried on according to the mathematical model and the use of experimental data，which show that the proposed algorithm with respect to the original genetic algorithm can improve the global search ability and convergence speed．

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更新日期/Last Update: 2018-05-15