Self-Organising Floor Plans in Care Homes

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...

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Main Authors: Silvio Carta, Stephanie St. Loe, Tommaso Turchi, Joel Simon
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Sustainability
Subjects:
Online Access:https://www.mdpi.com/2071-1050/12/11/4393
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spelling doaj-59bd2a035d644786ae1821716f4812292020-11-25T03:36:43ZengMDPI AGSustainability2071-10502020-05-01124393439310.3390/su12114393Self-Organising Floor Plans in Care HomesSilvio Carta0Stephanie St. Loe1Tommaso Turchi2Joel Simon3School of Creative Arts, University of Hertfordshire, College Lane, Hatfield AL10 9AB, UKSchool of Creative Arts, University of Hertfordshire, College Lane, Hatfield AL10 9AB, UKSchool of Creative Arts, University of Hertfordshire, College Lane, Hatfield AL10 9AB, UKMorphogen, 325 E 84th Street, New York, 10028 NY, USAThis 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.https://www.mdpi.com/2071-1050/12/11/4393care homesspatial layoutscare home designgenerative designgenetic algorithmsagent-based simulation
collection DOAJ
language English
format Article
sources DOAJ
author Silvio Carta
Stephanie St. Loe
Tommaso Turchi
Joel Simon
spellingShingle Silvio Carta
Stephanie St. Loe
Tommaso Turchi
Joel Simon
Self-Organising Floor Plans in Care Homes
Sustainability
care homes
spatial layouts
care home design
generative design
genetic algorithms
agent-based simulation
author_facet Silvio Carta
Stephanie St. Loe
Tommaso Turchi
Joel Simon
author_sort Silvio Carta
title Self-Organising Floor Plans in Care Homes
title_short Self-Organising Floor Plans in Care Homes
title_full Self-Organising Floor Plans in Care Homes
title_fullStr Self-Organising Floor Plans in Care Homes
title_full_unstemmed Self-Organising Floor Plans in Care Homes
title_sort self-organising floor plans in care homes
publisher MDPI AG
series Sustainability
issn 2071-1050
publishDate 2020-05-01
description 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.
topic care homes
spatial layouts
care home design
generative design
genetic algorithms
agent-based simulation
url https://www.mdpi.com/2071-1050/12/11/4393
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AT stephaniestloe selforganisingfloorplansincarehomes
AT tommasoturchi selforganisingfloorplansincarehomes
AT joelsimon selforganisingfloorplansincarehomes
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