Green Building Design Optimization Based on Multi-Objective Particle Swarm Algorithm
With the development of society and the growth of human demands, energy consumption is also continuously increasing. Green building energy-saving design is currently an important component in the field of energy consumption. It is also one of the current challenges that need to be addressed. To opti...
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| Vydáno v: | Engineering letters Ročník 33; číslo 10; s. 4098 |
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| Hlavní autor: | |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Hong Kong
International Association of Engineers
01.10.2025
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| ISSN: | 1816-093X, 1816-0948 |
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| Abstract | With the development of society and the growth of human demands, energy consumption is also continuously increasing. Green building energy-saving design is currently an important component in the field of energy consumption. It is also one of the current challenges that need to be addressed. To optimize the design of green buildings and reduce energy consumption while ensuring building comfort, a multi-objective green building energy-saving optimization model is constructed. An improved multi-objective back-bone particle swarm optimization algorithm based on adaptive disturbance factors is designed. To reduce the running time, a decomposition-based proxy model assisted multi-objective particle swarm optimization algorithm is designed. A new sample selection strategy guided by dual reserve sets is also designed. According to the experimental results, in single room and three bedroom buildings, the average hypervolume measurement values were 29311 and 49504, respectively. The average hypervolume measurement values of the proxy model were 21153 and 40230, respectively. The designed algorithm has good performance, which can provide technical support for the optimization design of green buildings. |
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| AbstractList | With the development of society and the growth of human demands, energy consumption is also continuously increasing. Green building energy-saving design is currently an important component in the field of energy consumption. It is also one of the current challenges that need to be addressed. To optimize the design of green buildings and reduce energy consumption while ensuring building comfort, a multi-objective green building energy-saving optimization model is constructed. An improved multi-objective back-bone particle swarm optimization algorithm based on adaptive disturbance factors is designed. To reduce the running time, a decomposition-based proxy model assisted multi-objective particle swarm optimization algorithm is designed. A new sample selection strategy guided by dual reserve sets is also designed. According to the experimental results, in single room and three bedroom buildings, the average hypervolume measurement values were 29311 and 49504, respectively. The average hypervolume measurement values of the proxy model were 21153 and 40230, respectively. The designed algorithm has good performance, which can provide technical support for the optimization design of green buildings. |
| Author | Yuan, Yousheng |
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| SubjectTerms | Adaptive algorithms Building design Clean energy Design optimization Energy conservation Energy consumption Green buildings Multiple objective analysis Optimization algorithms Optimization models Particle swarm optimization |
| Title | Green Building Design Optimization Based on Multi-Objective Particle Swarm Algorithm |
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