Search results for "NSGA II"
showing 2 items of 2 documents
A review on optimization and cost-optimal methodologies in low-energy buildings design and environmental considerations
2019
Abstract The topic of low-energy buildings received a widespread and growing interest in last years, thanks to energy saving policies of developed countries. The design of a low-energy building is addressed with energy saving measures and renewable energy generation, but the correct assessment of phenomena occurring in a building usually requires to perform dynamic simulations and to analyze multiple scenarios to attain the optimal solution. The optimality of a technical solution may be subject to contrasting constraints and objectives. For this reason, designers may employ mathematical optimization techniques, a non-familiar topic to most of building designers. In this paper, a review on o…
Multiobjective optimization of building energy consumption and thermal comfort based on integrated BIM framework with machine learning-NSGA II
2022
Detailed parametric analysis and measurements are required to reduce building energy usage while maintaining acceptable thermal conditions. This research suggested a system that combines Building Information Modeling (BIM), machine learning, and the non-dominated sorting genetic algorithm-II (NSGA II) to investigate the impact of building factors on energy usage and find the optimal design. A plugin is developed to receive sensor data and export all necessary information from BIM to MSSQL and Excel. The BIM model was imported to IDA Indoor Climate and Energy (IDA ICE) to execute an energy consumption simulation and then a pairwise test to produce the sample data set. To study the data set a…