Route Planning Based on Genetic Algorithm


  •  Lin Li    
  •  Yuhua Zhang    

Abstract

This paper mainly deals with the planning of aviation route and needs to determine the model to find out the shortest path. In this paper, we combine the methods of simulated annealing and genetic algorithm, and obtained the optimal solution method. Firstly, Genetic Algorithm (GA) uses the modified circle algorithm to find some feasible solutions to the approximate initial population, and then transforms them through simulated and crossover operations. This paper also introduces the aircraft fuel consumption model and the cubical smoothing algorithm with five-point approximation to reduce the aircraft fuel consumption and parts loss. The simulation results show that the accuracy of the route planning based on genetic algorithm is higher, while consumes less fuel and takes less sharp turns.


This work is licensed under a Creative Commons Attribution 4.0 License.