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

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Abstract

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.

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Acknowledgement

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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Correspondence to Jun-Qing Li or Pei-Yong Duan .

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Chen, X. et al. (2018). Research on Swarm Intelligence Algorithm Based on Prefabricated Construction Vehicle Routing Problem. In: Huang, DS., Jo, KH., Zhang, XL. (eds) Intelligent Computing Theories and Application. ICIC 2018. Lecture Notes in Computer Science(), vol 10955. Springer, Cham. https://doi.org/10.1007/978-3-319-95933-7_85

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  • DOI: https://doi.org/10.1007/978-3-319-95933-7_85

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95932-0

  • Online ISBN: 978-3-319-95933-7

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