Earlier studies in the context of windows and blinds selection have mostly tried to increase the awareness regarding various effects of windows and blinds selection on subjective well-being, including their effect on visual comfort, thermal comfort, energy consumption and life cycle cost. However, the main problem is the potential conflicts between visual comfort, thermal comfort, energy consumption and life cycle cost. Increased awareness about the contradictory effect of windows and blinds selection on subjective well-being on one hand and lack of a feasible method in managing the conflicts on the other hand may bind individuals, as decision-makers, in a situation where they follow the immediate economic benefits rather than the long-term visual and thermal benefits.
To solve the mentioned problem, this study analysed first the degree of the conflicts between average daylight illuminance and total energy consumption in Sweden. This decision was made due to large variation in solar elevation angle and solar intensity between summer and winter in Sweden, which has significant effects on daylight illuminance and total energy consumption. Analysing the conflicts was accomplished by developing two multivariate linear regression models for calculating average daylight illuminance and total energy consumption. Comparison and analysis of the multivariate linear regression models showed the existence of a high degree of conflicts, which makes window and blind selection a rather complex multidimensional problem.
Specifying the degree of the conflicts formed a hypothesis as: "A multi criteria decision-making method increases the controllability and manages the conflicts in selecting windows and blinds". The developed hypothesis was later tested by employing analytical hierarchy process, as widely used multi criteria decision-making method. The analytical hierarchy process prioritizes decision-maker' preferences and introduces a desired trade-off solution. The results of employing analytical hierarchy process showed the capability of it in managing the conflicts among visual comfort, thermal comfort, energy consumption and life cycle cost. Finally, the application of the analytical hierarchy process was expanded by integrating it with nondominated sorting genetic algorithm-II, as an optimization algorithm. Through this integration, optimization algorithm combines windows' and blinds' design variables and analyses a large number of solutions, while analytical hierarchy process ranks the solutions based on decision-makers' preferences and introduces a desired trade-off solution. The integration between analytical hierarchy process and the nondominated sorting genetic algorithm-II was presented later as a conceptual framework. The developed conceptual framework can be used for selecting windows and blinds in both residential and commercial buildings.
In selecting windows and blinds, the conceptual framework is a novel solution to the lack of a feasible method for increasing the controllability for decision-makers and obtaining a desired trade-off solution.
Article in journal (Refereed)
- Jalilzadehazhari, E., Mahapatra, K., Johansson, P. (2017). Increasing perceived control for enhancing subjective well-being in selecting windows and blinds : a conceptual framework. Architectural Engineering and Design Management.
- Jalilzadehazhari, E., Mahapatra, K. (2017). Multivariate linear regression model for estimating average daylight illuminance. Advanced Science Letters. 23. 6163-6167.
- Jalilzadehazhari, E., Johansson, P., Johansson, J., Mahapatra, K. (2017). Application of analytical hierarchy process for selecting an interior window blind. Architectural Engineering and Design Management. 13. 308-324.
Conference paper (Refereed)
- Jalilzadehazhari, E., Mahapatra, K. (2018). The most cost-effective energy solution in renovating a multi-family house. Cold Climate HVAC 2018, The 9th International Cold Climate Conference Sustainable new and renovated buildings in cold climates Kiruna – Sweden 12-15, March 2018.
- Jalilzadehazhari, E., Mahapatra, K. (2017). Multivariate linear regression model for estimating total energy consumption. The 3rd Asia conference of International Building Performance Simulation Association - ASim2016, Nov. 27-29, 2016, South Korea.
Licentiate thesis, comprehensive summary (Other academic)
- Jalilzadehazhari, E. (2017). Windows and blinds selection for enhancing subjective well-being. Licentiate Thesis. Växjö, Linnaeus University Press. 65.