Multi-target Phased Runway Scheduling Algorithm Research

For the rapid development of airline industry in China, there is a significant growth of air traffic flow. The original air traffic control system cannot satisfy the ever increasing traffic flow. As a result, significant delays and resulting environmental impacts are commonly observed during departure operations at major airports. One approach for mitigating airport congestion and delays is to exercise tactical operations planning and control with an objective to improve the efficiency of surface and terminal area operations.Departures and arrivals interact through the common use of airport resources. As the airport runway was identified to be a bottleneck for the departure flow because of the significance. If the runway's operational status has any improve, it will greatly benefit the efficiency of the whole system. Based on this, planning of runway operations was chosen in this thesis as the first problem to be investigated in an effort to begin addressing the overall surface operations planning problem using the method of decomposition. And it also be considered in the situation has multi-objective and multi-constraints. The research approach followed in the Departure Planner project at the Massachusetts Institute of Technology led to the work outlined in this thesis. The Departure Planner project has always been closely tied to Runway Operations Planning (ROP) since the project's goal is to conceptualize, design and develop a decision-aiding system for air traffic controllers, in order to assist them in optimizing departing traffic and closing unnecessary gaps between arrivals and departures and in general, performing their tasks in an integrated Ground Movement Planning System.First, as a subtask of planning airport surface operations, this thesis presents a thorough study of the structure and properties of the Runway Operations Planning problem, afterward a conceptual architecture for the Departure Planner system, which is the decision-aiding tool is proposed. And then, Runway Operations Planning is a workload-intensive task for controllers because airport operations involve many parameters, such as departure demand level that are typically characterized by a highly dynamic behavior. This research work provides insight to the nature of this task, by analyzing the different parameters involved in it and illuminating how they interact with each other and how they affect the main functions in the problem of planning operations at the runway, such as departure runway throughput and runway queuing delays. Analysis of the Runway Operations Planning problem revealed that there is a parameter of the problem, namely the demand"weight class", which: is more"dominant"on the problem performance functions that other parameters and changes value much slower than other parameters and its value is available earlier and with more certainty than the value of other parameters. These observations enabled the parsing of the set of functions and the set of parameters in subsets, so that the problem can be addressed sequentially in more than one stage where different parameter subsets are treated in different stages. Thus, a decomposition-based algorithm design technique was introduced and applied to the design of a heuristic decomposed algorithm for solving the ROP problem. This decomposition methodology offers an original paradigm potentially applicable to the design of solution algorithms for a class of problems with functions and parameters that, similar to those of the ROP problem, can be parsed in subsets. Finally, the performance behavior of the proposed"two-stage"ROP algorithm was evaluated with simulation tests implemented using Matlab and Simulink. The rationale for choosing Matlab is that it offers a robust programming environment, which also supports data structures, and the combination of Matlab and Simulink offers rapid prototyping capabilities and modularity. Thus, it is easy to make changes to the airport surface and runway geometry being modeled.