Structural Optimization for Masonry Shell Design Using Multi-objective Evolutionary Algorithms

In this study, the implementation of evolutionary algorithms to the form-finding problem of masonry shell models is presented using Autoclaved Aerated Concrete material. Regarding the significance of design decisions, the study is focused on the conceptual stage of the design process. In this context, the applied method is addressed as multi-objective real-parameter constrained optimization. For the sake of dealing with the shell design problem, two objective functions are considered: minimization of global displacement and minimization of mass. Two multi-objective evolutionary algorithms, namely, Non-Dominated Sorting Genetic Algorithm II and Real-coded Genetic Algorithm with mutation strategy of Differential Evolution Algorithms are compared in terms of computational and architectural performance. As a result, the solutions generated by these algorithms are found much competitive.

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