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27 August 2020 Research on Optimization of Port Logistics Distribution Path Planning Based on Intelligent Group Classification Algorithm
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Abstract

Meng, X. and Li, X., 2020. Research on optimization of port logistics distribution path planning based on intelligent group classification algorithm. In: Bai, X. and Zhou, H. (eds.), Advances in Water Resources, Environmental Protection, and Sustainable Development. Journal of Coastal Research, Special Issue No. 115, pp. 205-207. Coconut Creek (Florida), ISSN 0749-0208.

At present, the logistics industry has become an important part of social and economic development. The success of modern logistics enterprises depends on efficient cooperation with all upstream and downstream enterprises in the supply chain, and information technology is the prerequisite for such cooperation. Artificial Fish Swarm Algorithm (AFSA) is applied to robot path planning in intelligent bionic way. In order to improve the solving speed of the planning and reduce the length of the planning path, the convergence speed of the algorithm in the later stage is reduced and the local optimal solution is easily trapped. Location information is of great significance to the application of artificial fish swarm algorithm. The location of events or information sources is an important part of data transmission in sensor networks. The operation of the distribution system plays a vital role in the whole logistics system, and its analysis and design are the premise for its good operation.

©Coastal Education and Research Foundation, Inc. 2020
Xin Meng and Xuesong Li "Research on Optimization of Port Logistics Distribution Path Planning Based on Intelligent Group Classification Algorithm," Journal of Coastal Research 115(sp1), 205-207, (27 August 2020). https://doi.org/10.2112/JCR-SI115-064.1
Received: 16 February 2020; Accepted: 12 May 2020; Published: 27 August 2020
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