Big Data-Driven Genetic Algorithms for Dynamic Multi-Drone Route Optimization

This paper explores a novel approach to optimizing multi-drone delivery routes by integrating genetic algorithms (GA) with big data analytics. By leveraging real-time data, such as traffic, weather, and terrain information, the system dynamically adjusts routes, overcoming the limitations of static route planning. Simulations across various scenarios, including high-demand peaks and challenging terrains, demonstrate that the GA significantly improves both delivery efficiency and energy usage. Notably, the system shows strong scalability and adaptability to complex environments. Looking ahead, future research will focus on refining predictive capabilities and extending the system’s application to diverse terrains and evolving regulatory frameworks.