Research on Airline Routs Network Plannings based on Multi-objectives Optimization

At present, civil aviation transportation has rapidly increased and formed the air routes network, which can influence the travel cost of passengers. Route network planning not only has a great impact on the existing business activities of airlines, but also directly affects the company's future development and profitability. However, existing routes network is relatively scattered, and although the route coverage is wide, the depth is insufficient, which leaks the optimization method after the establishment of network. In this work, we use an innovative multi-objective optimization framework that combines a genetic algorithm and a simulated annealing algorithm to find the best trade-offs between multiple targets. Our approach takes into account not only the direct operating costs of the route, but also indirect costs such as the costs associated with flight delays and environmental taxes. Through the experimental analysis of different routes, we demonstrate the effectiveness of our method. The results show that our optimization framework can effectively improve the overall efficiency of the route network while reducing the environmental impact. In addition, the framework has good flexibility to adapt to changing market conditions and passenger needs.