Human circadian rhythm varies with different combinations of light sources. Natural light and dark patterns regulate the sleeping and waking cycles of the human body. This study aimed to develop a simplified model for daylight glare and circadian entrainment in an existing controlled daylight-artificial light integrated system. In addition, the effects of window orientation, occupant position, artificial light, daylight, and a combination of both on Circadian Stimulus (CS) were investigated. In

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... a daylit interior space, window orientation, shading control and occupant seating position play a significant role in the CS. Simplified models to predict Daylight Glare Probability (DGP) and CS were estimated from the dataset. The developed nonlinear CS estimation models have R-squared values of 0.983 and 0.974. The precision of the models was evaluated in terms of standard error of regression (S) and AIC score. Multi-Objective Genetic Algorithm based optimization technique was developed using the above models to minimize glare and maximize CS in the working space. This optimisation methodology aids in implementing a complete automation algorithm for the test workbench to achieve visual comfort and circadian entrainment. INDEX TERMS Circadian stimulus, vertical eye illuminance, daylight glare probability, non-linear regression models, multi-objective genetic algorithm optimization.