## 2 Multi-Objective Message Routing in EnFVs
### Importance of Multi-Objective Optimization in EnFVs  
There is a critical need to develop routing algorithms that can effectively optimize message routing in these dynamic transportation systems and address the limitations of traditional routing algorithms [18]. Multi-objective optimization is highly important in the context of EnFVs due to several key reasons [10; 14; 23]:  
* Conflicting objectives: EnFVs face multiple conflicting objectives that need to be optimized simultaneously. These objectives may include maximizing energy efficiency, minimizing travel time, reducing emissions, optimizing battery usage, ensuring pas-senger comfort, and considering safety and regulatory constraints. Multi-objective optimization allows for balancing and trade-off analysis among these objectives to find the most desirable solutions.
* Complex and dynamic environment: EnFVs operate in complex and dynamic environments, such as urban areas with varying traffic conditions, weather patterns, and the availability of charging or refueling infrastructure. Multi-objective optimization techniques enable the vehicles to adapt to these changing conditions and make informed decisions to optimize performance based on multiple objectives.
* Resource constraints: EnFVs often have limited resources, such as battery capacity or fuel availability. Multi-objective optimization helps in finding optimal solutions that make efficient use of these resources by considering multiple objectives simultaneously. It allows for better resource allocation and utilization, thereby extending the range and overall performance of EnFVs.
* User preferences and stakeholder considerations: Different stakeholders, including vehicle owners, operators, passengers, and regulatory bodies, may have diverse preferences and requirements. Multi-objective optimization provides a systematic approach to incorporate these preferences and consider the needs of various stakeholders while optimizing the vehicle's performance. It allows for the generation of a set of Pareto-optimal solutions, offering a range of choices that can cater to different user preferences and stakeholder considerations.
* Innovation and future development: Multi-objective optimization serves as a catalyst for innovation and the development of advanced EnFV technologies. By exploring various trade-offs and finding optimal solutions, it encourages the integration of cutting-edge technologies, such as advanced energy management systems, intelligent routing algorithms, and vehicle-to-vehicle communication, to achieve the best possible performance across multiple objectives. This drives the progress and advancement of EnFV technologies for a sustainable and efficient transportation system.  
In summary, multi-objective optimization is crucial in the context of electric and flying vehicles as it enables the vehicles to address conflicting objectives, adapt to dynamic environments, optimize resource usage, consider user preferences and stakeholder considerations, and drive innovation for future development. It plays a vital role in achieving optimal performance and advancing the sustainability of EnFVs in the transportation sector.