[1]金仙力,李金刚.基于遗传算法的多目标路径优化算法的研究[J].计算机技术与发展,2018,28(02):54-58.[doi:10．3969/j．issn．1673－629X．2018．02．013]
　JIN Xianli,LI Jingang.Research on Multi－target Path Optimization Algorithm Based on Genetic Algorithm[J].,2018,28(02):54-58.[doi:10．3969/j．issn．1673－629X．2018．02．013]
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基于遗传算法的多目标路径优化算法的研究()
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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02期
页码:
54-58
栏目:
智能、算法、系统工程
出版日期:
2018-02-10

文章信息/Info

Title:
Research on Multi－target Path Optimization Algorithm Based on Genetic Algorithm
文章编号:
1673－629X(2018)02－0054－05
作者:
金仙力; 李金刚
南京邮电大学 计算机学院 软件学院，江苏 南京 210003
Author(s):
JIN Xian－li; LI Jin－gang
School of Computer Science and Technology，School of Software，Nanjing University of Posts and Telecommunications，Nanjing 210003，China
关键词:
物流; 车辆路由问题; 时间约束; 遗传算法; 收敛
Keywords:
logistics; vehicle routing problem; time constraints; genetic algorithm; convergence
分类号:
TP301.6
DOI:
10．3969/j．issn．1673－629X．2018．02．013
文献标志码:
A
摘要:
物流行业在发展过程中存在着许多制约因素，比如车辆路由问题(VＲP)等。VＲP 的目标是以一个最小的成本服务于一系列服务点。对此，提出一种基于遗传算法的路径优化算法，用以解决服务点有序且带时间约束条件的车辆路由问题。首先，根据问题建立相应的模型，并将遗传算法运用到问题求解当中;然后，通过添加算子调节等操作来改进遗传算法，增加了算法的适用范围，加快了算法的收敛速度，提高了算法的效率;最后，将算法应用于实际生活当中，并与传统的遗传算法进行对比。结果表明，改进后的算法收敛速度更快、效率更高，能够有效地解决服务点有序且带时间约束条件的车辆路由问题。
Abstract:
There are many constraints in the development of the logistics industry，such as vehicle routing problem (VＲP)，the goal of which is to serve a range of service points at a minimum cost．For this，we propose a path optimization algorithm based on genetic algorithm for the VＲP with orderly service point and time constraints．First of all，we establish the corresponding model according to the problem，and apply the genetic algorithm for problem solving．Then，the genetic algorithm is improved by adding operator adjustment and other operations，increasing its application range，accelerating its convergence speed and rising its efficiency．Finally，the algorithm is applied to real life and compared with traditional genetic algorithm，which shows that it can effectively solve the VＲP with service point order and time constraints，with faster convergence speed and higher efficiency．

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更新日期/Last Update: 2018-03-27