Research on the Application of Linearization Model Methods in Low Altitude Airspace Planning

This paper investigates the issue of conflict resolution between spatiotemporal conflict airspace requirements in low-altitude airspace planning. Regarding to the complex constraints of this multi-objective optimization problem, the quadratic constraints in the problem are relaxed by linear approximation method and the mixed-integer linear multi-objective programming model is established through absolute value linearization and multidimensional Boolean product linearization methods. Subsequently, specific scenarios are designed, and the user airspace application data is simulated. Using the solver to analyze the simulation data, and the results indicate that as the demand scale increases, the solving time increases exponentially, and the solving effectiveness gradually declines after exceeding a certain scale. Finally, through the analyzing of the linear relaxation method, combining with specific data, the deviation of the model from the actual problem is calculated. Due to the relatively small theoretical error, it is proven that this linearized model is applicable to solving the low-altitude airspace conflict resolution problem.