Hybrid Genetic Algorithm Based on Machine Learning and Fitness Function Estimation Proposal for Ground Vehicle and Drone Cooperative Delivery Problem

In this study, the development of a hybrid genetic algorithm, integrating machine learning and function estimation, presents a novel approach to address the simultaneous intervention challenge involving unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs). The adaptability of this hybrid genetic algorithm confers a notable advantage in managing drone scenarios. Notably, this work constitutes the inaugural attempt in the literature to devise an exact solution for the concurrent intervention of a UGV and a UAV, with the added innovation of minimizing intervention time. This pioneering methodology holds promise for extending the problem domain to encompass more realistic scenarios, thereby bridging a significant gap in the literature and furnishing a foundational framework for future research endeavors.