Efficient Routing Strategies for Electric and Flying Vehicles: A Comprehensive Hybrid Metaheuristic Review

The integration of electric and flying vehicle (EnFV) systems has ushered in a new era of transportation, offering promising solutions for reducing carbon emissions and improving urban mobility. However, optimizing routing in these systems poses significant challenges due to their multi-objective nature, including minimizing energy consumption, travel time and ensuring safety. In this study, we explore applying hybrid metaheuristic approaches as a viable solution to tackle the complex routing optimization problem in EnFV systems. By combining multiple metaheuristic algorithms, these hybrid approaches can offer improved performance and efficiency, contributing to the sustainable evolution of transportation systems. We present an in-depth analysis of this domain's state-of-the-art research, methodologies, and promising results. The paper discusses the background and related work in routing optimization for EnFV systems, highlights various metaheuristic algorithms and their limitations, and introduces hybridization techniques to address the challenges of multi-objective optimization. Real-world case studies demonstrate the successful implementation of hybrid metaheuristic approaches in routing optimization. Performance evaluation and analysis of the advantages and trade-offs of hybridization provide valuable insights into the effectiveness of these approaches. Furthermore, the paper identifies challenges specific to EnFV routing and explores potential areas for future research and enhancements to hybrid metaheuristic techniques. In conclusion, the review underscores the significance of routing optimization in EnFV systems and emphasizes the potential of hybrid metaheuristics to shape the future of sustainable and optimized transportation systems.