AA EmTech tutor Milad Showkatbakhsh and AA Alumni Mohammed Makki and Diege Navaro-Mateu have published a research article in TAD Journal: Decoding the Architectural Genome: Multi-Objective Evolutionary Algorithms in Design.

The research article investigates the application of population-based optimization algorithms in design. This method is heavily driven by the translation and analysis of various data sets that represent a design problem; in evolutionary-based algorithms, these data sets are illustrated through two primary data streams: genes and fitness functions. The latter is frequently examined when analysing the algorithm’s output, and the former is comparatively less so.

The paper also examines the role of genomic analysis in applying multi-objective evolutionary algorithms (MOEA) in design. The results demonstrate the significance of utilizing the genetic analysis to understand better the relationships between parameters used in the design problem’s formulation and differentiate between morphological differences in the algorithmic output not commonly observed through fitness-based analyses.

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Image: Schematic phenotypic outcomes associated with genomic analysis by colour gradients. Courtesy of Milad Showkatbakhsh