Towards Multi-Objective Optimization for Sustainable Buildings with Both Quantifiable and Non-Quantifiable Design Objectives
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ASCE. Architectural design can be seen as a multi-objective optimization process, aimed at finding optimal solutions for multiple, often conflicting objectives. Despite the significant advancements of multi-objective optimization methods and building modeling technologies, multi-objective optimization has not been enabled for building design in practice. The reasons include: 1) the complexity of fitness evaluation for quantifiable objectives, such as structural, economical, and sustainable performance objectives, in which a large number of building design decision variables are discrete, nonlinear, and stochastic; and 2) the missing of non-quantifiable objectives of overriding significance to architects, e.g. aesthetic, social, and cultural objectives in optimization. The research objective of this research is to discover how to develop a parametric BIM-based, multi-objective optimization framework with both quantifiable and non-quantifiable objectives, and how it can search for Pareto Optimal design solutions with diverse non-quantifiable objective measures to assist architects' decision-making.
