The Application of Evolutionary, Generative, and Hybrid Approaches in Architecture Design Optimization

Abstract

Since the emergence and application of evolutionary optimization approaches in architecture in the early twentieth century, a wide range of studies have attempted to integrate evolutionary strategies with the design process. The extensiveness and dispersion of research in this field and the growing application of the generative evolutionary techniques in solving design problems necessitate analytical classification of pertinent literature review. Based on the descriptive-analytical review of the literature on generative evolutionary strategies in architecture, this paper proposes a research model for an integrated generative design framework to enhance future application of this approach in the conceptual design stage. Therefore, first, selected 140 journal articles, with key-words exploration method, between 2014 and 2020 is analyzed to categorize the applied techniques, identify the gap, and address the issue of selecting the appropriate evolutionary approach in the early stage of design. Literature analysis is classified into seven topics, each demonstrating shortcomings of related studies in four categories of form finding, Spatial Programming, Performance-based optimization, and Multi-objective optimization. The research results indicate a growing interest in applying hybrid methods, multi-objective optimization problems, the need for an integrative generative evolutionary framework in the early design phase, and a conceptual design tools with Co-simulation possibility.