This study investigates an NP-hard parallel machine scheduling problem, a critical challenge in manufacturing, healthcare, and logistics industries where efficient resource allocation is essential. The issue involves scheduling operations where each task requires an additional resource, with...

This study introduces an approach to improving the utilization of solar energy in facilities by integrating advanced machine learning (ML) techniques into solar power scheduling. Traditional methods, often constrained by static schedules, fail to adequately adapt to the inherently dynamic and...