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Multi-objective optimisation of path and space utilisation in landscape garden green space design

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Publicado en:PLoS One vol. 20, no. 7 (Jul 2025), p. e0326374
Autor principal: Yu, Jia
Otros Autores: Song, Jiazhe, Lan, Huihui, Zhang, Yugui
Publicado:
Public Library of Science
Materias:
Green infrastructure
Urbanization
Urban environments
User experience
Pheromones
Population density
Algorithms
Optimization techniques
Mutation
Landscape architecture
Efficiency
Urban areas
Layouts
Multiple objective analysis
Objectives
Design
Ant colony optimization
Foraging behavior
Pareto optimum
Aesthetics
Genetic algorithms
Design optimization
Optimization algorithms
Gardens & gardening
Economic
Acceso en línea:Citation/Abstract
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Resumen:This study addresses the multi-objective optimization problem in landscape garden green space design, focusing on optimizing space utilization efficiency, path efficiency, and aesthetic quality. We compare various multi-objective optimization algorithms to solve the problem We compare various multi-objective optimization algorithms to solve the problem, applied to the urban environment of Tongzhou District, which is characterized by rapid urbanization and high population density. Experimental results demonstrate that MOEAs outperforms other optimization algorithms such as GA, PSO, ACO, and SA in all three objectives. Specifically, MOEAs achieved a space utilization efficiency of 90.2%, a path length of 140.3 m, and an aesthetic quality score of 9.2, surpassing the best results from GA (85.3%, 150.2 m, 8.4), PSO (88.5%, 148.6 m, 8.6), ACO (82.4%, 160.5 m, 7.9), and SA (80.1%, 162.4 m, 7.5). In conclusion, MOEAs provides a superior solution for optimizing landscape garden green space design, offering the best balance between spatial efficiency, path optimization, and aesthetic quality, particularly for urban areas like Tongzhou.
ISSN:1932-6203
DOI:10.1371/journal.pone.0326374
Fuente:Health & Medical Collection