a novel design-based optimization method for building by sensitivity analysis

The important objective of a building must be to provide a comfortable environment for people. heating ventilation and air conditioning systems provide a comfortable environment but they have high energy consumption. therefore, designing an energy-efficient building that balances energy performance and thermal comfort is necessary. choosing effective parameters for energy performance is an important factor in achieving this goal. this research aims to produce a methodology for multi-objective optimization of daylight and thermal comfort in order to study the effect of wall material and shading of an office building (tehran a basic-location). the building simulation was developed and validated by comparing predicted daylight and thermal comfort hours based on tests and training in jupiter notebook. the sensitivity analysis uses a multiple linear regression method. secondly, optimization is based on a genetic algorithm with effective parameters to optimize daylight and thermal comfort performance. for this, we developed a parametric model using the grasshopper plugin for rhino and then used honeybee and ladybug plugins to simulate thermal comfort and daylight, and finally used octopus engine to find an optimization solution. the result of this paper is essential as a preliminary analysis for building optimization in the open-plan office.