Research On Optimal Scheduling Method Of The Special Electric Vehicle Working On Parking Apron

With the rapid development of civil aviation of china,passenger volume of the airports has been gradually increasing,and the number of the special vehicle in parking apron has been also increasing.March 2015,the work of Civil Aviation Administration of China that the airport special vehicle change from electric-driven to fuel-driven has begun,and some airports has started to use the special electric vehicle.Predictably,the special electric vehicle will become more widespread in the future Airport.This will bring new demands and challenges to the electric vehicle scheduling problem.The scheduling method of the special electric vehicle will different from the special oil-fueled vehicle because of the structural characteristics of it.The vehicle networking technology and the intelligent algorithm for the vehicle scheduling provides a new way to solve this problem.In the thesis,a new method called decision-planning is proposed to solve the scheduling problem of the special electric vehicle,which is divided into two layers: the decision-making layer and the path-planning layer.It is decided which vehicle is suitable for carrying out the task in the decision-making layer,and decision result is input into the path-planning layer.In the path-planning layer,the problem is the same as Travelling Salesman Problem of n cities.Through the combination optimization algorithm,the optimal objective function is constructed to meet the constraints,and the global optimal path of the vehicle routing problem is obtained.Because the ID3(Iterative Dichotomiser 3)algorithm is simple and easy to understand,and it spends less time on constructing decision tree.It constructs the task allocation model by the ID3 algorithm in the thesis.In order to improve the probability of convergence to the global optimization and improve convergence speed,An improved Hopfield neural network—the Full Feedback Hopfield neural network(FFCHNN)is proposed.It is shown that the FFCHNN has better performance and higher efficiency than the traditional HNN,when it is used to solve the TSP problem,by analyzing the results of the simulation.The algorithm is used as the optimal combination algorithm for path planning of the take vehicle in the thesis.Finally,the scheduling example of electric tool vehicle is solved by the decision-planning method.The results show that this method can decides the vehicle suitable for execution more precisely,and gets the shortest path of the vehicle.The decision-planning method is new scheme for solving the problem of the electric vehicle scheduling in the airport.