Self-Organising Floor Plans in Care Homes

Silvio Carta, Stephanie St. Loe, Tommaso Turchi and Joel Simon
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Silvio Carta: School of Creative Arts, University of Hertfordshire, College Lane, Hatfield AL10 9AB, UK
Stephanie St. Loe: School of Creative Arts, University of Hertfordshire, College Lane, Hatfield AL10 9AB, UK
Tommaso Turchi: School of Creative Arts, University of Hertfordshire, College Lane, Hatfield AL10 9AB, UK
Joel Simon: Morphogen, 325 E 84th Street, New York, NY 10028, USA

Sustainability, 2020, vol. 12, issue 11, 1-16

Abstract: This paper presents and discusses an optimisation approach applied to spatial layouts in care home building design. With this study, we introduce a method for increasing the floor plan efficiency using a self-organising genetic algorithm, thus reducing energy consumption, improving the wellbeing of residents and having an implicit impact on the costs of energy and health care. In order to find an optimal spatial configuration, we elaborated and tested a number of design criteria based on existing literature reviews and interpreted through initial considerations of care home layouts. These are used as objectives in a Genetic Algorithm (GA) to evaluate the best design solution. The self-organised floor plan is then used to run a final simulation to observe how residents could use the optimised spaces and to measure the improved efficiency of the new plans. The paper concludes with the discussion of the results and some considerations for future studies and experiments using emergence behaviour models to improve sustainable development in design.

Keywords: care homes; spatial layouts; care home design; generative design; genetic algorithms; agent-based simulation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
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