Morphological Multi-Objective Optimization of Traditional Dwellings in Southern Xinjiang Based on Genetic Algorithms: A Case Study of the Suohema House

Traditional dwellings in southern Xinjiang, exemplified by the Suohema House, have evolved as adaptive responses to the region’s cold and arid climatic conditions, providing thermally comfortable living environments with relatively low energy consumption. Learning from these climate-responsive design strategies offers an effective approach to reconciling the conflict between energy efficiency and indoor comfort. Such exploration is of great significance for preserving regional architectural identity and promoting the development of low-carbon buildings. This study establishes a performance-driven morphological multi-objective optimization framework for traditional dwellings, taking building energy consumption, thermal comfort, and indoor temperature as the primary optimization objectives. The framework integrates parametric modeling, performance simulation, and multi-objective optimization within the Rhino & Grasshopper platform, employing a genetic algorithm to achieve performance-oriented design exploration. Key design variables were identified through data analysis, and the influence weights and prioritization of morphological parameters were quantified. The results reveal that the room depth in residential dwellings (4.57–4.73 m), room width (3.97–6.75 m), room clear height (2.33–2.42 m), wall thickness (lower wall thickness ranging from 1.14 to 1.22 m, upper wall thickness at 0.76 m), and building orientation (true south) have significant impacts on both energy consumption and indoor thermal performance. Based on these findings, adaptive optimization strategies were proposed from three perspectives: scale optimization, spatial hierarchy refinement, and enhancing the performance of building envelopes. The proposed framework provides methodological guidance for the conservation and adaptive renewal of traditional dwellings, as well as for the design of new, green, and low-carbon residential buildings suited to the climatic conditions of southern Xinjiang.

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Publication Details

Journal
Buildings
Published
2025-12-12
DOI
https://doi.org/10.3390/buildings15244497
Primary Topic
Building Energy and Comfort Optimization
Type
article
Field-Weighted Citation Impact
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article

Morphological Multi-Objective Optimization of Traditional Dwellings in Southern Xinjiang Based on Genetic Algorithms: A Case Study of the Suohema House

Buildings
Building Energy and Comfort Optimization
article

Morphological Multi-Objective Optimization of Traditional Dwellings in Southern Xinjiang Based on Genetic Algorithms: A Case Study of the Suohema House

article en

Abstract

Traditional dwellings in southern Xinjiang, exemplified by the Suohema House, have evolved as adaptive responses to the region’s cold and arid climatic conditions, providing thermally comfortable living environments with relatively low energy consumption. Learning from these climate-responsive design strategies offers an effective approach to reconciling the conflict between energy efficiency and indoor comfort. Such exploration is of great significance for preserving regional architectural identity and promoting the development of low-carbon buildings. This study establishes a performance-driven morphological multi-objective optimization framework for traditional dwellings, taking building energy consumption, thermal comfort, and indoor temperature as the primary optimization objectives. The framework integrates parametric modeling, performance simulation, and multi-objective optimization within the Rhino & Grasshopper platform, employing a genetic algorithm to achieve performance-oriented design exploration. Key design variables were identified through data analysis, and the influence weights and prioritization of morphological parameters were quantified. The results reveal that the room depth in residential dwellings (4.57–4.73 m), room width (3.97–6.75 m), room clear height (2.33–2.42 m), wall thickness (lower wall thickness ranging from 1.14 to 1.22 m, upper wall thickness at 0.76 m), and building orientation (true south) have significant impacts on both energy consumption and indoor thermal performance. Based on these findings, adaptive optimization strategies were proposed from three perspectives: scale optimization, spatial hierarchy refinement, and enhancing the performance of building envelopes. The proposed framework provides methodological guidance for the conservation and adaptive renewal of traditional dwellings, as well as for the design of new, green, and low-carbon residential buildings suited to the climatic conditions of southern Xinjiang.

BuildingsVol. 15(24)
Tarim University (CN), Zhejiang University (CN)
National Office for Philosophy and Social Sciences
Affordable and clean energy
Openalex Percentile: Top 42%
Building Energy and Comfort Optimization
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Morphological Multi-Objective Optimization of Traditional Dwellings in Southern Xinjiang Based on Genetic Algorithms: A Case Study of the Suohema House · Buildings (2025) | TGRS Research Map | TGRS