# Study on Multi-Objective Optimization-Based Climate Responsive Design of Residential Building
## 2 Background and Literature  
### The Logic of Building Climate Responsive Optimization Design  
The building climate responsive design strategy aims to study the climate control methods applicable to the building comfort space. By considering the climate differences in different places and using appropriate strategies to improve the occupants' thermal comfort, the building environment is adjusted in order to providing a comfortable indoor thermal environment for human daily activities. In this method, the choice of building technology is based on the relationship between external climatic conditions and human needs [1; 2; 3]. In order to quantitatively analyze the environmental benefits of building climate responsive design, the research proposes an optimization process based on building simulation, integrates building performance simulation and optimization, and implements a reverse search for optimal performance parameters. Architectural design is essentially an optimization problem. Architects are constantly improving the design based on existing means to meet the design requirements in the best way which is an iterative process [4; 5]. In general, the design process can be divided into two main stages: the divergent stage, which is mainly to generate conceptual alternatives; and the convergence stage, which is mainly used to evaluate and select the best conceptual design from the proposed alternatives. In all stages of design, from the conceptual design stage to the detailed design stage, the steps of divergence and convergence are always repeated. Until the end of the design phase, the number of alternatives gradually decreased, leaving only one or a few solutions. This iterative process is the process of design exploration, which aims to study and develop the design space and provide information for decision-making throughout the design process, as shown in Figure 1.  
The traditional architectural design process does not have an integrated system and method in the early scheme divergence stage and the late convergence stage. Architectural design in the traditional sense is always judged based on the architect's experience, and the architect's cognitive level determines whether the project can achieve the expected objectives. When the design problem involves a large number of complex variables, it is difficult to achieve the optimal goal only by the architect's subjective judgment. The development of today's building simulation technology can effectively assist designers in making decisions to eliminate uncertain assumptions in the design process to a certain extent, and quantitatively evaluate the design scheme. However, these procedures are quite complicated, and the data required for calculation is very detailed, which is difficult to obtain in the early stage of the design, so the relevant scheme can only be evaluated in the later stage of the design. Most of the decisions that have a significant impact on energy consumption are made in the early design stage. Therefore, in the traditional design process, it is difficult to effectively assist the building climate responsive design by relying solely on these simulation programs [6; 7]. The study proposes the use of optimized search methods based on building environment simulation. More in detail, based on building simulation tools, a Monte Carlo simulation framework was established to analyze and search the uncertainty of the input parameters, and use automation to solve the problem that it is difficult to determine the input parameters in the traditional sense. Figure 1: (**a**): divergent and convergent stage; (**b**): repetition of divergence and convergence; (**c**): scenario exploration process. Optimization is the process of finding the best combination of different solutions when the given constraints are met. The execution of optimization requires decision variables, objective functions, and constraints. The Equation (1) expresses the general mathematical optimization process. \[