Flexible search and optimization in parametric design

Today architectural design processes are more and more influenced by parametric methods. As these allow for a multiplicity of alternatives, the design process can be enriched by computational optimization. Extensive research has shown the efficiency of optimization in engineering and design disciplines. Though, optimization is hereby rather a technical than a design task; it is limited to different autonomous specialist areas and does not enable a comprehensive approach. Advanced optimization methods facilitate the generation of complex systems, but these procedures are directed and do not provide turnoffs, multiple solutions or altering circumstances. These however are things that are essential for architectural design processes, which mostly do not have clearly defined starting and end points. This practice subdivides the workflow into two independent and recurring tasks: the generation of a parametric model followed by optimization of its driving parameters. The result is then assessed with respect to its actual qualities. The design either is kept, or modifications on the parametric model, its auxiliary conditions and parameters are made and the optimization process starts again from scratch. Our aim is the development of a flexible generation and optimization framework for practical use in the sense of a continuously accompanying design explorer, in which parameterization is adaptable and objective functions are changeable at any time during the design process. The user is supported in his/her understanding of correlations by identifying a multiplicity of optimal solutions utilizing state-of-the-art multi-objective search algorithms within the core of the framework. Considering the tool as an interactive design aid, an intuitive interface allowing for extensive manual guidance and verification of the search process is featured. Zooming, filtering and weighting within the genotypic, phenotypic and objective space comply with an extensive support of man-machine-dialogue and incorporation of non- or not-yet quantifiable measures. A reusable search history aids examination of design alternatives and the redefinition of constraints maintaining the continuity of the search process and traceability of results in the sense of a rational design verification. Within this work it is not planned to focus on specific optimization targets, but to build an open framework to allow for all kinds of objective functions and in particular the mediation between conflicting targets. An open and intuitive process should be established, applicable in real-world modes of operation that satisfies increasingly complex correlations of modern architecture`s requirements as a powerful extension of classical design methods.

New paradigms and tools for the computer aided modelling of designs are at the forefront of research in architecture. Easier than ever, software environments for visual scripting now enable a parametric description of geometry, allowing quick alterations of the result. The promotion of biologically inspired optimization methods for such parameterized designs is a main goal of this research project. Evolution of life on earth has proved very efficient in its way to solve many problems and in our research serves as the main way to search for solutions in tasks formulated with a parametric design definition. Simulation of realworld behaviour such as structural,geometric, or solar performance in these formulations adds valuable economic aspects to such an optimization. Inspiration from other disciplines such as computer science, mathematics, and interface design led to the development of novel components for an established digital design environment of the architectural engineering industry. Computer algorithms which already proved their efficiency in other fields have been brought into the realm of nonexpert users of digital design software, enabling new modes of search and optimization. The main advances are a smooth workflow with the embedding in a familiar environment, the possibility to negotiate multiple goals while leaving the final decision between the generated proposals to the user, and deepened control and insight into the optimization process itself. The tools are published online as freeware plugins, where feedback of academic and professional users around the world indicates large interest in means for computeraided design optimization. Our methods have been applied successfully in many academic and real world projects, which encourages further research in the field. It is speculated on novel ways of digital representation and optimization by the use of methods from artificial intelligence and applied mathematics, potentially overcoming some of the main problems found in the current approaches and easing efficient design even more.