The article presents the application of Hybrid Evolutionary and Greedy-based algorithms to the problem of Automated Floor Plan Generation. The described optimization issue is part of a wider domain of Computer-Aided Architectural Design. The article covers the extensive description of the representation domain model (architectural canonical guidelines, user design requirements and constraints) and the explanation of proposed approach: problem representation, genetic algorithm operators, and fitness function definition. The research experimental procedures are based on real-world data: the architectural design guidelines being the design constraints and five real-world functional programs introduced and proposed as benchmarks. The article summarizes the implementation of the proposed approach, compares the Hybrid Evolutionary Algorithm experimental results with the Greedy-based algorithm, and suggests possible extensions and future research directions.
This article is an overview focused on functionality and usability of selected contemporary approaches for the computational floor plan generation of architectural objects. This article describes current solutions for generative architectural design and focuses on their usability from the point of view of architectural design practice. Recent research papers and prototypes, as well as the most important tools (selected computer-aided design and BIM software) for generative design from the architectural perspective, are described. The functionalities and level of usability of present-day software and prototypes are described. In addition, the descriptive review of the research prototypes architectural design outcomes is present. Furthermore, the survey among active architects regarding the usage of computational tools in the professional practice and possible guidelines for the development of such tools are present. This article summarises with the conclusion about the current state of generative floor plan design tools, the lack of fully functional and developed commercial tools of this type on the market and future directions for the development of generative floor plans tools.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.