Improved Methods for Solving the Electric Vehicle Charging Scheduling Problem to Maximize the Delive

In this paper, we present an improved methodology for scheduling electric vehicle (EV) charging at a single charging station, taking into account vehicle arrival and departure times, as well as drivers' charging requirements. The objective is to minimize the difference between desired and final state-of-charge levels while adhering to constraints on power capacity and charger availability. As electric vehicles increasingly contribute to mitigating greenhouse gas emissions, efficient charging strategies become crucial to manage their impact on the electrical grid. Our study delves into the complex task of scheduling EV charging at public stations, where drivers pre-communicate their charging needs. This study proposes improved solution methods, including a standalone mathematical programming model for scheduling, a hybrid heuristic algorithm for assignment, which combines mathematical modeling techniques for evaluation and energy allocation, and a hybrid tabu search algorithm, which uses the same mathematical model employed in the heuristic. Our results demonstrate the effectiveness of our approach in tackling the challenges of EV charging scheduling, highlighting its relevance for sustainable energy management.