Optimization design of internal space layout of three-bedroom residential apartment based on IGA and DE algorithm

To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the...

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Vydáno v:PloS one Ročník 20; číslo 7; s. e0326153
Hlavní autoři: Zhao, Ling, Li, Baijun
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States Public Library of Science 07.07.2025
Public Library of Science (PLoS)
Témata:
Adaptability
Algorithms
Analysis
Apartments
Architects
Architecture
Behavior
Binary codes
Biology and Life Sciences
Building information modeling
Cognitive psychology
Computer and Information Sciences
Design
Design and construction
Design optimization
Ecology and Environmental Sciences
Efficiency
Evolutionary algorithms
Facility Design and Construction - methods
Fitness
Genetic algorithms
Global optimization
Housing
Humans
Immunoglobulin A
Internal layout
Kinematics
Layouts
Mathematical optimization
Methods
Models, Theoretical
Optimization algorithms
Optimization models
Optimization techniques
Physical Sciences
Quality of life
Research and Analysis Methods
Room layout (Dwellings)
Shortest-path problems
Smart buildings
Social Sciences
User feedback
User needs
User satisfaction
Utilization
China
ISSN:1932-6203, 1932-6203
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Popis
Shrnutí:To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. The model characterizes room functions and spatial locations through binary coding, and uses dynamic fitness function and backtracking strategy to improve space utilization and functional fitness. In the experiments, optimization metrics such as kinematic optimization rate (calculated based on the shortest path and connectivity between functional areas), space utilization rate (calculated by the ratio of room area to total usable space), and functional fitness (based on the weighted sum of users’ subjective evaluations and functional matches) all perform well. Quantitatively, it is found that the model achieves 94.76% in terms of motion optimization rate, the highest space utilization rate is 96.6%, functional fitness is 9.4, and user satisfaction is close to 94.21%. The optimization results show that the proposed method has significant advantages in improving space utilization and meeting personalized design needs. However, despite the good optimization results, the method still faces the problem of improving the optimization ability under high-dimensional space and complex constraints. This study provides an efficient solution for intelligent building layout design and has certain practical value.
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Competing Interests: The authors have declared that no competing interests exist.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0326153