## 2 Multi-Objective Message Routing in EnFVs  
Message routing plays a critical role in facilitating efficient communication and data exchange in transportation systems, including EnFVs [13]. However, traditional routing algorithms often fail to consider the unique characteristics and requirements of these emerging modes of transportation [12]. EVs require a careful consideration of energy consumption, charging station availability, and range limitations, while flying vehicles such as drones need to navigate airspace regulations, flight restrictions, and congestion. Therefore, there is a need for specialized routing approaches that address the specific objectives and constraints of these vehicles.  
In recent years, researchers have explored the application of multi-objective optimization techniques to address the challenges of message routing in EnFVs. Multi-objective optimization aims to find a set of solutions that simultaneously optimize multiple objectives, considering trade-offs between them [14]. GAs are inspired by the process of natural selection and evolution [15]. They operate on a population of potential solutions, represented by chromosomes, and iteratively improve them through selection, crossover, and mutation operations. By applying these genetic operators, the algorithm explores the solution space, considering different combinations of objectives and constraints. The use of GAs in multi-objective message routing for EnFVs has been investigated in several studies. For example, [PERSON] and [PERSON] [16] proposed a GA-based approach that optimized message routing for EVs, considering objectives such as considers reliability, data rate, and residual energy as routing metrics. Their results demonstrated significant improvements of up to 90% in packet delivery rate using New York City traffic trace.  
In the context of FVs, [PERSON] et al. [6] applied a GA to optimize message routing for flying ad hoc networks (FANETs). Their approach focuses on improving the routing in FANETs to enhance network performance and lifetime. They proposed the GA-based routing (GAR) protocol, which considers factors like stability, link bandwidth, and node energy. By utilizing a GA approach, GAR quickly identifies optimized routes, resulting in improved network performance. The simulation results show that GAR enhances route stability, thereby improving overall network performance and increasing network availability. However, the paper acknowledges the need to incorporate energy consumption in future research to develop energy-efficient routing strategies. Overall, the GAR protocol offers a promising solution for enhancing routing in FANETs, with potential implications for network sustainability and efficiency. This study highlighted the effectiveness of GAs in addressing the multi-objective nature of message routing for EnFVs. By considering multiple objectives and constraints simultaneously, GAs can generate a set of solutions that represent trade-offs between different optimization goals. These solutions offer decision-makers a range of routing options that cater to various objectives, such as minimizing energy consumption, maximizing efficiency, and adhering to operational constraints.  
In conclusion, multi-objective message routing in EnFVs requires specialized approaches that consider the unique characteristics and objectives of these modes of transportation.