<p>This study introduces a mathematical modeling framework specifically designed for electric vehicles (EVs) to tackle intricate challenges in real-world transportation scenarios, focusing on two critical areas: parking optimization and vehicle scheduling. The first component centers on developing a mathematical model for optimizing vehicle placement within parking lots to minimize maneuvering costs that significantly impact parking efficiency. This model enhances the overall effectiveness of parking space utilization by strategically determining vehicle positioning. The second aspect addresses idle time minimization for charging electric vehicles through the idle time minimization for electric vehicle charging scheduling model. This mathematical model efficiently schedules multiple EVs by dynamically assigning charging slots based on arrival and departure times and the charging station's capacity, thereby reducing waiting time and improving the charging infrastructure's efficiency. The real-time vehicle scheduling optimization model also focuses on the dynamic management of vehicle scheduling, assigning vehicles to service tasks while considering vehicle availability, time constraints, and energy levels. Numerical examples are provided to substantiate the proposed models, illustrating their practical applications and validating their reliability and effectiveness in optimizing vehicle management systems. The study concludes by examining the spatial distribution of vehicles and ideal assignments, demonstrating how these mathematical models facilitate informed decision-making in real-time, ultimately contributing to enhanced operational efficiency in vehicle management systems.</p>