Research on Swarm Intelligence Algorithm Based on Prefabricated Construction Vehicle Routing Problem

  • Xingrui Chen
  • Jun-Qing LiEmail author
  • Yongqin Jiang
  • Yunqi Han
  • Kun Jiang
  • Xiaoping Lin
  • Pei-Yong DuanEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10955)


Prefabricated buildings are becoming increasingly popular in China. Logistics distribution is an important aspect of their deployment. At present, there are few logistics management issues, and the logistics and distribution problems are gradually increasing. The planning of path problems is also one of the issues that many scholars are concerned about. With the attention of many experts, a single intelligent optimization algorithm fails to achieve the optimal path and does not apply to large-scale and complicated path planning. Of the existing swarm intelligence algorithms, the ant colony algorithm is the most widely studied one, whereas other swarm intelligence algorithms or hybrid swarm algorithms are relatively less studied. This study combines the research of swarm intelligence algorithms at home and abroad, and thus presents a comprehensive review and analysis of the swarm intelligence algorithms proposed by scholars, which is of significant theoretical importance for the solution of realistic path optimization problems.


Assembly building Swarm intelligence Ant colony algorithm Logistics and distribution 



This research is partially supported by the National Science Foundation of China (61773192, 61503170, 61603169, 61773246), Shandong Province Higher Educational Science and Technology Program (J17KZ005, J14LN28), Natural Science Foundation of Shandong Province (ZR2016FL13, ZR2017BF039), 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

  • Xingrui Chen
    • 1
  • Jun-Qing Li
    • 1
    • 2
    • 3
    • 4
    Email author
  • Yongqin Jiang
    • 3
  • Yunqi Han
    • 3
  • Kun Jiang
    • 3
  • Xiaoping Lin
    • 3
  • Pei-Yong Duan
    • 2
    Email author
  1. 1.School of InformationShandong Normal UniversityJinanChina
  2. 2.School of ComputerLiaocheng UniversityLiaochengChina
  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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