The Research Of Joint Resource Management For Apron Under The Condition Of Integrated Monitoring Technology

Gates and special equipment are the core resources in airport operations. Efficient and rational use of Gates and special equipment will directly affect the operational efficiency of the airport. For a long time, when the traditional methods were developed to guide resource allocation scheme, the scheduling costs of the equipment were always ignored, or little consideration of whether the flight demand matches with the attributes of the resources was given, which lead to operation cost was too high in the implementation of the plan. At the same time, the plan was forced to temporarily change and the produce organizations were confused in the airport. Because of those above, ground security services for flights was not completed timely and widespread delays of flights was caused. The apron resource management involves two aspects of aerodrome operation safety and efficiency optimization So, apron resource managers urgently need a scientific and practical approach which is guidance for resource allocation and management of gates and special equipment.To make up for the deficiencies of the existing guidance methods, apron joint resource management problem was put forward. In this problem, the lowest cost of the first-level and the second-level scheduling were considered in the implementation of the plan. Improving the quality of service and reducing the operation cost were regarded as the premise. A multi-objective optimization model was established, and according to this model, a genetic algorithm was designed. Passenger walking distance, aircraft taxiing costs and special equipment service were considered as objectives in this model. In order to solve the multi-objective optimization problem, using the genetic algorithm, parameter coding, initial population, fitness function, genetic operation and related parameters were ingeniously designed. And the global optimality was maintained, at the same time, the speed of problem-solving was increased. In the actual operations, the equipment can affect the execution of normal flight service, also the arrival costs during execution. Taking this into account, a key decision variable was introduced to the equipment scheduling cost of the model, which took the value of either1or infinity. With this variable, the equipment costs and the service arrival costs could be calculated. Together with other objections, they could evaluate the pros and cons of the schedules.Determining the cost of the second-level scheduling was a key point of problem-solving. Considering the types and models of special equipment, the surrounding environment of the service lanes, the types and the surrounding space of the gates, this article proposes a method of conflict detection in support of comprehensive monitoring technique, which is able to determine the value of decision variable. If and only if a conflict is detected, the decision variable is infinite, otherwise the value is1. In the study of conflict detection method, the techniques of collision and road accessibility detection were used to realize the conflict recognition, a model relating to the service equipment and the service lanes of apron was established, a conflict detection algorithm was designed. Then a simulation was made, combined with a database built. The method for determination of the key decision variable of special equipment service arrival costs was verified. The results showed that a warning message would be sent when service equipment and other obstructions or equipment were detected in conflict in actual operations, the decision variable took the value of infinity, so the equipment service arrival costs were infinite, which represented an infeasible planConsidering the accuracy, integrity and reliability, comprehensive monitoring technique was able to support for the determination of the cost The simulation conclusion shows, the method was feasible to determine the cost of the second-level scheduling. In addition, the method, which was used to determine the cost of the second-level scheduling, can be used for real-time monitoring the status and the schedule implement process.