Work

Low-Carbon Water Ecological POI Logistics Route Planning Based on Improved Water Network Space AGNES Clustering Model and Symmetrical Simulated Huffman Spatial Searching Tree Algorithm

Year: 2025

Type: article

Abstract: To reduce the pollutant emissions of water ecological POI logistics, the water ecological POI logistics route-planning method based on the improved water network space AGNES clustering model and the symmetrical simulated Huffman spatial searching tree (SHSST) algorithm is innovatively established. The improved AGNES algorithm is established for water ecological POI clustering, and then the logistics distribution center location model based on water ecological POI clustering is constructed. On the basis of an optimal distribution center, combining the symmetrical feature of vehicle moving paths and distances in logistics sub-intervals and logistics intervals, the sub-interval optimal route-searching algorithm based on the symmetrical SHSST is constructed to determine the optimal path for each logistics sub-interval, and then the global logistics route-planning algorithm based on undirected complete graph spatial search is constructed to search for the global optimal logistics route. Experiments prove that the proposed algorithm can accurately cluster water ecological POIs and output the logistics route with the lowest costs and pollutant emissions. Compared to the traditional AGNES and other clustering algorithms, the improved AGNES algorithm has lower time complexity. Compared to the traditional logistics route algorithms, SHSST has lower algorithm complexity, route costs, and pollutant emissions, and strong stability. The minimum and maximum optimization rates for the same route are 10.06% and 17.58%, while the minimum and maximum optimization rates for the optimal route are 11.41% and 14.29%; it could effectively reduce the negative impact of pollutants on the water ecological environment and POIs.

Source: Symmetry

DOI: 10.3390/sym17111894

Authors: Xiao Zhou, Fan Jiang, Wenbing Liu, Jun Wang

Institutions: Xihua University, Leshan Vocational and Technical College, PLA Army Service Academy

Language: English

Topic: Vehicle Routing Optimization Methods

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Clean water and sanitation, Sustainable cities and communities, Industry, innovation and infrastructure, Responsible consumption and production, Climate action

Open Access status: gold

Estimated APC paid: $2,896