Journal
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
Volume 18, Issue 11, Pages 3072-3082Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TITS.2017.2673247
Keywords
Multi-objective air traffic network flow optimization (MATNFO); route and time-slot assignment (RTA); route searching module (RSM); time-slot refinement module (TRM); pre-selection operator (PO)
Categories
Funding
- National Science Foundation for Young Scientists of China [61401011]
- National Key Technologies R&D Program of China [2012BAG04B01]
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Air traffic flow management (ATFM) aims to facilitate the utilization of airspace and airport resources and is critical in air transportation systems. During the past decades, several challenging problems have arisen from this domain and attracted intensive studies. This paper addresses the problem of alleviating the airspace congestion and reducing the flight delays in ATFM simultaneously. We formulate this problem as a multi-objective air traffic network flow optimization (MATNFO) problem. In this MATNFO model, comprehensive ATFM actions, for instance, ground-holding, airborne-holding, rerouting, and speed control, are considered. Meanwhile, a systematic approach, namely route and time-slot assignment (RTA) algorithm, is developed to solve the MATNFO problem. The idea of divide-and-conquer is embedded in the algorithm by sequentially applying both route searching module and time refinement module. Furthermore, for the sake of efficiency, a pre-selection operator is proposed as one heuristic strategy to identify promising solutions and reduce the search space by defining a sector equilibrium metric. Experiments on real data of the Chinese airspace show that the RTA algorithm outperforms an existing competitor and three related multi-objective evolutionary algorithms. In addition, RTA is competent for high-quality real-time air traffic network flow assignment.
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