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Applying a decision-making framework for resolving conflicts when selecting windows and blinds
Linnaeus University, Faculty of Technology, Department of Forestry and Wood Technology.ORCID iD: 0000-0003-1835-7158
Linnaeus University, Faculty of Technology, Department of Forestry and Wood Technology.ORCID iD: 0000-0003-0130-3356
Linnaeus University, Faculty of Technology, Department of Built Environment and Energy Technology.ORCID iD: 0000-0003-4405-1056
2018 (English)In: Architectural Engineering and Design Management, ISSN 1745-2007, E-ISSN 1752-7589Article in journal (Refereed) Epub ahead of print
Abstract [en]

The selection of the most appropriate window and blind design is a challenging task due to the existence of potential conflicts between visual comfort, thermal comfort, energy consumption and life cycle cost. Resolving these conflicts relies on a trade-off window and blind design. This research applied a decision-making framework to select a trade-off window and blind design for an office room in Sweden. The decision-making framework was developed based on integrating the non-dominated sorting genetic algorithm-II and the analytical hierarchy process. The first step in the application of the framework was to generate a model of the office room using EnergyPlus. Six types of window and four types of blind; an internal venetian blind, an internal roller curtain, an external venetian blind and an external overhang panel, were modelled in EnergyPlus. The second step was to run an optimisation using non-dominated sorting genetic algorithm-II. For this purpose, various window and blind design variables were specified in modeFRONTIER platform. The third and last step in the application of the decision-making framework was to select a trade-off window and blind design using analytical hierarchy process. The results show the strength of the decision-making framework in selecting a trade-off design, and thereby the ability to resolve conflicts through intelligent use of simulation in analyzing big-data in built environment, energy and cost sectors. Since, the computation and processing power for performing simulations is constantly increasing, architects and designers can exploit the decision-making framework and locate a trade-off design in a relatively short period of time.

Place, publisher, year, edition, pages
Taylor & Francis, 2018.
Keywords [en]
Decision-making, big data, optimisation, non-dominated sorting genetic algorithm II, analytical hierarchy process, trade-off design
National Category
Architectural Engineering
Research subject
Technology (byts ev till Engineering), Sustainable Built Environment
Identifiers
URN: urn:nbn:se:lnu:diva-79039DOI: 10.1080/17452007.2018.1550383OAI: oai:DiVA.org:lnu-79039DiVA, id: diva2:1267358
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ProWood
Funder
Knowledge Foundation, 20130245Available from: 2018-12-01 Created: 2018-12-01 Last updated: 2018-12-03

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Mahapatra, Krushna

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Jalilzadehazhari, ElahehJohansson, JimmyMahapatra, Krushna
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3233343536373835 of 92
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