Multi-objective Optimization of Bio-based Thermal Insulated Panels using Evolutionary Algorithms

Sustainability has been continuously incorporated into the building policies and regulations of several countries. However, this has led to a complexity in the application of these regulations and the determination of optimum parameters for different projects. In this context, the use of a method such as multi-objective optimisation is particularly interesting. For this study, a workflow that includes the OpenBIM methodology was used in the calculation model generation procedure. A total of nine parameters were used in JEPlus for the optimisation of a case study, evaluating more than 500,000 design options. The objective functions to be minimised were initial cost and Global Warming Potential (GWP) during 50 years of the building's life cycle. For all best solutions that had a cost between USD $ 2,500 -$10, 500 with GWP ranging of 1 - 62 tonCO2, the type of thermal insulation material played a key role along with its thickness. Insulating materials such as EPS and Glass wool were then compared with a Bio-based insulated material, using Evolutionary Algorithms and JEA, an Interactive Optimisation Engine. The interoperability between the software and the effectiveness of the optimisation algorithms have allowed for an expansive comparison to predict models that cannot otherwise be explored with conventional methods. Finally, based on the results, a new construction system based on digital manufacturing was prototyped.