Activity-based models (ABMs) face a critical limitation: their utility functions often oversimplify human decision-making by focusing narrowly on travel time and cost, while neglecting key behavioral factors like environmental impact, health outcomes, and weather-related discomfort. To bridge this gap, we propose a utility function that systematically integrates these overlooked determinants while incorporating personalized weightings to reflect individual priorities for optimizing daily activity schedules within an ABM framework. Compared to traditional approaches, our utility function provides a more holistic representation of human preferences. The resulting framework offers researchers and planners an adaptable tool for optimizing activity schedules in ways that align with contemporary sustainability, health, and comfort considerations.