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Application of Ant Colony Algorithms to Solve the Vehicle Routing Problem

  • Mei-xian Song
  • Jun-qing Li
  • Li Li
  • Wang Yong
  • Pei-yong Duan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10954)

Abstract

Many optimization problems exist in the world. The Vehicle Routing Problem (VRP) is a relatively complex and high-level issue. The ant colony algorithm has certain advantages for solving the capacity-based vehicle routing problem (CVRP), but is prone to local optimization and high search speed problems. To solve these problems, this paper proposes an adaptive hybrid ant colony optimization algorithm to solve the vehicle routing problem with larger capacity. The adaptive hybrid ant colony optimization algorithm uses a genetic algorithm to adjust the pheromone matrix algorithm, designs an adaptive pheromone evaporation rate adjustment strategy, and uses a local search strategy to reduce computation. Experiments on some classic problems show that the proposed algorithm is effective for solving vehicle routing problems and has good performance. In the experiment, the results of different scale issues were compared with previously published papers. Experimental results show that the algorithm is feasible and effective.

Keywords

Ant colony system Genetic algorithm Shortest path Vehicle routing problem 

Notes

Acknowledgement

This research is partially supported by National Science Foundation of China under Grant 61773192, 61773246, 61603169 and 61503170, Shandong Province Higher Educational Science and Technology Program (J17KZ005), Key Laboratory of Computer Network and Information Integration (Southeast University), Ministry of Education (K93-9-2017-02), and State Key Laboratory of Synthetical Automation for Process Industries (PAL-N201602).

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Mei-xian Song
    • 1
  • Jun-qing Li
    • 1
    • 2
    • 3
    • 4
  • Li Li
    • 1
  • Wang Yong
    • 1
  • Pei-yong Duan
    • 2
  1. 1.School of ComputerLiaocheng UniversityLiaochengChina
  2. 2.School of InformationShandong Normal UniversityJinanChina
  3. 3.China Key Laboratory of Computer Network and Information IntegrationSoutheast University, Ministry of EducationNanjingPeople’s Republic of China
  4. 4.State Key Laboratory of Synthetical Automation for Process IndustriesNortheastern UniversityShenyangChina

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