| Against the backdrop of the global issue of climate change,energy saving and carbon reduction in the field of architecture have gradually received attention.As the quality of life continues to improve,users have become increasingly demanding of the indoor environment of buildings.Traditional single-target optimization design in architecture can no longer meet the current design needs.In recent years,more and more scholars have conducted building performance simulation research based on dual-objective or triple-objective optimization.However,research problems such as the lack of methods for determining architecture performance optimization variables and difficulties in selecting the optimal design from nondominated solution sets obtained through multi-objective optimization still need to be solved.Some researchers have used objective weighting methods to make decisions on multi-objective optimization results,but this weakens the architect’s voice in selecting the design scheme.Therefore,the subjective value of the architect’s personal design perspective and the creation of spatial atmosphere cannot be ignored when it comes to building design and optimization.To address these research gaps,this paper studies the multi-objective optimization decision-making method for architectural design based on the architect’s perspective.Firstly,in response to the problem of the lack of methods for determining optimization variables from the architect’s perspective in existing multi-objective optimization research on buildings,we surveyed China’s current building energy-saving design standards and national energy-saving policies in the building sector.This study summarized the key points of building performance optimization design and future development directions in China,and also studied the characteristics of building performance optimization problems in residential,office,and educational buildings through summarizing core literature in the field of architecture in the past five years.This study concluded the key parameter sets for building performance optimization problems in China and proposed a method for determining building performance optimization variables from the architect’s perspective.Secondly,the process of building multi-objective optimization and decision-making are improved.In the optimization process,this study comprehensively and in detail reviewed optimization methods and tools based on proxy models.In the decision-making stage,this study introduced a multi-attribute decision-making method based on a combination of subjective and objective weighted-TOPSIS evaluation to evaluate and select building performance optimization solutions.This method can scientifically integrate the architect’s subjective design intention into the decision-making process while maintaining the rationality of the data distribution when facing high-dimensional complex decision-making problems.It realizes the evaluation and decision-making of solutions from the architect’s perspective.To verify the proposed decision-making method in this paper,this study took primary and secondary school buildings in cold regions as an example.this study selected the building life cycle carbon emissions,building operating energy consumption,and the percentage of natural lighting as optimization objectives.This study used BP-neural networks combined with genetic algorithms to perform multi-objective optimization and then used the TOPSIS evaluation model based on subjective and objective weighted combinations to rank and make decisions.This study validated the method from the perspectives of superiority of weighting and effectiveness of decision-making results.Finally,this study proved that this method is suitable for decisionmaking on building multi-objective optimization problems. |
