Route Planning, Air Refueling Aircraft Based On Genetic Algorithm

Air-refueling is the process which requires the tanker aircraft to make oil supply for the deploying aircraft during the journey without landing.Under the modern military condition of integrative combined operations,implementing air refueling between different war zones and different army services will be more frequent,the capability of air-refueling is more and more important to the air force of different nations.Journey planning is a core of air refueling and its aim is to optimize different targets such as the total fuel consumption,the flight distance of the deploying aircraft and safety of air-traffic considering the influence of the allocation of war zones and the influence of weather. The specialty of air refueling leads to the specialty of journey planning. Some problems such as how to so]ve the model using algorithms and how to effectively solve it are very important theoretically and practically and will be useful to the construction of modern military in China.Under the systematic analysis of air refueling problem,a journey-planning model is constructed.This model considers the total fuel consumption and the flight distance of the deploying aircraft.Aimed at defects of traditional optimization methods,GA(Genetic Algorithm) is proposed to solve the air refueling journey planning model.Based on natural selection and genetic mechanism,GA is an algorithm with characteristics of global optimization and parallelism.It make up defects of traditional optimization methods.So a GA based method is proposed to solve this model.Because of some defects in standard Genetic Algorithms,auto-adaptive punishment is proposed and according to the specialty of the model,some critical techniques,such as coding method, constraints-handling technique,genetic operator design and algorithm efficiency optimization method,are studied.By making use of global optimization character,the problem related to nonlinear restriction and convergence in local area is solved.Using GA and its programs,the practices prove the efficiency of GA and put forward an optimizing solution for the journey programming problem by computing and comparing the results based on the journey-based mode and area-based mode.