Indoor Comfort and Energy Consumption Optimization Using an Inertia Weight Artificial Bee Colony Algorithm

A comfortable indoor environment contributes to a better quality of life and wellbeing for its occupants. The temperature, lighting, air are the main controlling factors user comfort levels. optimum control conditioners, ventilators helps in maximizing user’s level. Nonetheless, energy consumption these appliances needs be taken into consideration minimize operational cost at same time provide an environmentally friendly system. Comfort level maximization minimization optimization problems. This issue is becoming more important due lifestyle changes caused by COVID-19 pandemic that resulted spent home indoors. Inertia weight artificial bee colony (IW-ABC) algorithms using linearly increasing, decreasing, exponentially increasing inertia proposed here index usage. multi-objective problem tackled as weighted single objective problem. solution tested dataset 48 environmental conditions. results simulation show IW-ABC performs than original ABC other benchmark with linear has most improved convergence behavior.