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Computational tools for early architectural design need to address issues related to building performance and integrally consider early design decisions regarding building form, spatial layout, orientation, and envelope articulation. This paper presents (1) a design optimization tool, Multiobjective Architectural Design Explorer (MADE) that supports performative-based building design, and (2) a design exploration strategy that effectively operationalizes MADE for Pareto-based comparative search. MADE implements genetic optimization in two steps. It first generates building layouts that satisfy formal, topological, and placement constraints with a single-objective genetic algorithm. Then, MADE determines the opening sizes of the generated layout(s) by optimizing the buildings' energy and daylighting performance with a multiobjective genetic algorithm.MADE is tested on the design of a library building and the proposed Pareto-based exploration strategy is demonstrated in the selection of an optimal design. The results point out the feasibility of the presented tool and the design strategy, and that multiple objectives can be satisfied by sequentially optimizing design objectives. [ABSTRACT FROM AUTHOR]

This work introduces Evolutionary Architectural Space layout Explorer (EASE), a design tool that facilitates the optimization of 3D space layouts. EASE addresses architectural design exploration and the need to attend to many alternatives simultaneously in layout design. For this, we use evolutionary optimization to find a balance between divergent exploration and convergent exploitation. EASE comprises a novel sub-heuristic that constructs valid spatial layouts, a mathematical framework to quantify the satisfaction of constraints, and evolutionary operators to improve alternative layouts' fitness. We test EASE on the design of a library building. We evaluate EASE's performance for different building forms and different evolutionary algorithm parameters. The results suggest that EASE can generate valid layouts, quantify the constraints' degree of satisfaction and find a number of optimal layout solutions. The layouts that EASE generates are intended not as end results but design artifacts that provide insight into the solution space for further exploration. [ABSTRACT FROM AUTHOR]