Integrating Multi-Criteria Decision Analysis in Luminaire Selection Based on Colour Preferences and Energy Consumption
Year: 2024
Type: article
Abstract: \nΟptimizing colour balance preference and energy efficiency simultaneously is often difficult. Despite advancements in technology enhancing energy efficiency, harmonizing colour preference with energy conservation remains complex. This study investigates the interaction among colour preference, energy efficiency, evaluation frameworks to improve understanding and design practices. Using a methodical approach, research employs multi-criteria decision analysis (MCDA) to optimize colour preference and energy efficiency in lighting design. A computational tool based on genetic algorithms is used to generate nine distinct spectral power distributions (SPDs) with similar Correlated Colour Temperatures (CCT) and average fidelity but varying in gamut shape and size. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), an MCDA method, is then applied to assess colour evaluation systems. TOPSIS compares alternatives based on pre-specified criteria, aiding in the selection of lighting luminaires that balance colour preferences and energy consumption. The study’s findings provide recommendations and expand the discourse on lighting design practices. Future research may explore alternative decision analysis methodologies to refine evaluation frameworks. Harmonizing colour preference with energy efficiency is vital for environmental sustainability and user satisfaction. Strategic methodologies like MCDA and computational tools support the balance of aesthetic preferences and environmental consciousness, promoting sustainable lighting solutions.\n
Authors: Anastasios Dimitrakis, Evangelos-Nikolaos Madias, Athanasios Kotsenos, Frangiskos V. Topalis
Institution: National Technical University of Athens
Language: English
Topic: Color perception and design
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W6940710146
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