Design optioneering: multi-disciplinary design optimization through parameterization, domain integration and automation of a genetic algorithm

The overall performance of buildings is heavily impacted by design decisions made during the early stages of the design process. Design professionals are most often unable to explore design alternatives and their impact on energy profiles adequately during this phase. Combining parametric modeling with multi-disciplinary design optimization has been previously identified as a potential solution. By utilizing parametric design and multi-disciplinary design optimization to influence design at the schematic level in the interest of exploring more energy efficient design configurations, the H. D. S. Beagle 1.0 tool was developed. The tool enables the generation of design alternatives according to user defined parameter ranges; automatically gathers the energy analysis result of each design alternative; automatically calculates three objective functions; and uses Genetic Algorithm to intelligently search, rank, select, and breed the solution space for decision making. Current case studies demonstrate our tool's ability to reduce design cycle latency and improve quality. However, the future work is needed to further investigate how to acclimate this process to accommodate early design stages and processes.