Process-driven Bim-based Optimal Design Using Integration of Energyplus, Genetic Algorithm, and Pareto Optimality

This paper addresses optimal architectural design using BIM at the design stage. We present a comparative study of the differences between datacentric and process-driven interoperability approaches during the design phases. The authors will elaborate on two approaches, summarize their consequences, and present a real application of the approach using a DAI (Design Analysis Integration) prototype (Augenbroe et al, 2003) based on processdriven interoperability in a schematic design stage. To solve a multi-criteria optimal design problem of a BIM-based energy performance simulation model, we use Genetic Algorithm (GA) and Pareto optimality. The term ““optimal design”” refers to the selection of various exterior double glazing systemsfor minimizing energy use and satisfyingthermal comfort. The software EnergyPlus 6.0 developed by DOE (U.S Department of Energy) was used for energy and comfort simulation. The integration of GA, Pareto optimality and EnergyPlus 6.0 simulation runs was automatically performed in the MATLAB platform. The results of this study indicate that meaningful information can be delivered to DM based on process-driven interoperability using BIM and GA with Pareto optimality.