Application And Research Of Improved Genetic Algorithm In Military Flight Task

With the development of science and technology and its application in military tasks,military task planning is becoming more and more scientific,accurate and efficient.The mission planning system is widely used in many military fields,including unmanned combat platform,deep space exploration,the cruise missile long-range precision strike,multi aircraft cooperative combat,high resolution of Earth Observation of the military field.Mission planning in route planning is one of the very important part during the mission,the information provided to the driver is complicated,only rely on the pilot itself to consider a number of factors,and then make a decision and planning is not possible.Therefore,an intelligent route planning function is needed to assist the pilot to make real time decision.The route planning is to find the optimal route of the aircraft from taking off position to landing position and satisfying the specific performance index and constraint conditions.These specific properties include the planning of the route away from the threat of the source,and in the case of security to achieve the shortest distance,time consuming.Due to the limitation of fuel and flight tasks,the time of flight must be limited to a certain period of time.Therefore,more and more scholars have studied the flight mission planning of aircraft.First,this paper analyzes the domestic and foreign research situation of military flight route planning,and comprehends the advantages and disadvantages of the various algorithms applied to aircraft flight route planning,finally we chose the genetic algorithm and improve it.The improved genetic algorithm is applied to route planning.In this paper,genetic algorithm is introduced and analyzed in detail.The advantages and disadvantages of traditional genetic algorithm are listed.Three optimization methods are put forward aiming at the shortcomings of traditional genetic algorithm.(1)In order to improve the selection operation,a hybrid selection mechanism using different selection methods at different times is adopted.In the initial selection,tournament and elitism reserved selection methods were adopted.In the later stage of evolution,roulette selection strategy was adopted.This hybrid selection method can avoid premature convergence.(2)In order to improve the cross operation,Using the similarity between the two parent genes determines whether or not they are intersecting,when the two parent genes' similarity degree is low,they will be exchanged.This method can avoid the destruction of the good genes and the slow speed of convergence.(3)In order to improve the mutation operation,it adjusts the mutation probability.When the individual fitness is large,it will give the individual a small mutation probability,make it possible to maintain good genes.If the individual fitness is small,will give the individual a larger mutation probability,in order to enable the individual to move closer to the excellent individuals.This method can avoid local convergence.Finally,the improved genetic algorithm is applied to the flight route planning to be put forward in this paper,under the same conditions,the experimental results with the traditional genetic algorithm,the experimental results are compared.The data shows that the improved genetic algorithm in terms of the running time and the optimal path is superior to the traditional genetic algorithm.It proves that the improved method proposed in this paper is effective.