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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:

30

期数:

2020年12期

页码:

170-175

栏目:

应用开发研究

出版日期:

2020-12-10

文章信息/Info

Title:

Research on Vehicle Routing Problem Based on Improved Dragonfly Algorithm

文章编号:

1673-629X(2020)12-0170-06

作者:

陶文瀚¹; 赵晨聪¹; 孙翌博²; 刘晨磊³; 孙知信¹; 孙 哲¹

1. 南京邮电大学 现代邮政学院 &现代邮政研究院,江苏 南京 210003; 2. 常州工学院 计算机信息工程学院,江苏 常州 213032; 3. 南京邮电大学 宽带无线通信与传感网技术教育部重点实验室,江苏 南京 210003

Author(s):

TAO Wen-han¹; ZHAO Chen-cong¹; SUN Yi-bo²; LIU Chen-lei³; SUN Zhi-xin¹; SUN Zhe¹

1. School of Modern Posts & Institute of Modern Posts,Nanjing University of Posts and Telecommunications,Nanjing 210003,China; 2. School of Computer Science and Information Engineering, Changzhou Institute of Technology,Changzhou 213032,China; 3. Key Lab of Broadband Wireless Communication and Sensor Network Technology of Ministry of Education,Nanjing University of    Posts and Telecommunications,Nanjing 210003,China

关键词:

物流配送; 车辆路径问题; 时间窗; 蜻蜓算法

Keywords:

logistics distribution; vehicle routing problem; time window; dragonfly algorithm

分类号:

TP301

DOI:

10. 3969 / j. issn. 1673-629X. 2020. 12. 030

摘要:

随着现代物流业的高速发展,物流配送过程中的车辆路径问题已经成为影响物流行业发展的关键因素。 为了实现在物流配送过程中有效地提高配送效率,减少车辆的空车行驶率和行驶距离,降低运输成本,提出了一种改进型蜻蜓算法。 将随机学习优化的思想融入到传统蜻蜓算法中,优化了原算法存在的收敛精度低、最优解容易陷入局部收敛等缺陷,并将该算法应用到带软时间窗约束的车辆路径问题上。 首先根据配送货物的运输成本、仓库的驻留成本、超时惩罚成本等因素,构建出一种综合成本最小化的车辆路径问题的数学模型,并用该算法对该问题进行求解。 然后通过系统仿真模拟构建最优路径,并与其他智能优化算法进行对比分析,证实了该算法的有效性和可行性,同时也证明了该算法在求解带软时间窗约束的车辆路径问题上有着较好的性能。

Abstract:

With the rapid development of the modern logistics industry,the problem of vehicle routing in the logistics distribution process has become a key factor affecting the development of the logistics industry. In order to effectively improve the distribution efficiency,reduce the empty rate and distance of vehicles,and reduce transportation costs during the logistics distribution process,we propose    an improved dragonfly algorithm that incorporates the idea of random learning optimization into the traditional dragonfly algorithm. The disadvantage of the original algorithm such as low convergence accuracy and easily falling into local convergence of optimal solution is optimized. The algorithm is applied to vehicle routing problems with soft time window constraints. Firstly,a mathematical model  of the comprehensive cost minimization of vehicle routing problem is constructed based on factors such as the transportation cost of the delivered goods,the resident cost of the warehouse and the cost of overtime penalties,and the proposed algorithm is used to solve the problem.Then the optimal path is constructed through system simulation, and compared with other intelligent optimization algorithms, the effectiveness and feasibility of the proposed algorithm are verified. At the same time,it also proves that the proposed algorithm has better performance in solving vehicle routing problems with soft time window constraints

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更新日期/Last Update: 2020-12-10