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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2020  >  20(6): 218-226
TIAN Wen, YANG Fan, YIN Jia-nan, SONG Jin-jin. Multi-objective optimization method of air route space-time resources allocation[J]. Journal of Traffic and Transportation Engineering, 2020, 20(6): 218-226. doi: 10.19818/j.cnki.1671-1637.2020.06.019
Citation: TIAN Wen, YANG Fan, YIN Jia-nan, SONG Jin-jin. Multi-objective optimization method of air route space-time resources allocation[J]. Journal of Traffic and Transportation Engineering, 2020, 20(6): 218-226. doi: 10.19818/j.cnki.1671-1637.2020.06.019
shu

Multi-objective optimization method of air route space-time resources allocation

doi: 10.19818/j.cnki.1671-1637.2020.06.019

  • School of Civial Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, Jiangsu, China

Funds:

National Natural Science Foundation of China 71971112

National Natural Science Foundation of China 61903187

National Natural Science Foundation of China 52002178

Natural Science Foundation of Jiangsu Province BK20190416

Natural Science Foundation of Jiangsu Province BK20190414

Fundamental Research Funds for the Central Universities kfjj20190717

More Information
  • Author Bio:

    TIAN Wen(1981-), female, lecturer, PhD, tw1981@nuaa.edu.cn

  • Received Date: 2020-08-06
  • Publish Date: 2020-06-25
    Abstract
  • To improve the degree of collaborative decision-making between airlines and air traffic controllers, as well as reduce the level of flight delays, air route flights were used as a research object and the multi-objective allocation of route space-time resources was studied. The effects of uniqueness, time sequence, and feasibility constraints of flights under actual operating conditions were considered and the flight trajectory and entry time slot assigned by the flight in the restricted area were viewed as decision variables. The lowest total flight delay cost and the lowest airline delay fair loss deviation coefficient were regarded as objective functions. A multi-objective nonlinear 0-1 integer programming model was constructed. Based on the characteristics of the model reference, the non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ) was used and an integer gene encoding scheme was designed by the permutation encoding method. A feasible solution set was generated to maximize genes. To verify the validities of the model and algorithm, based on the South China sea area flight operation example, the performance of searching for the optimal solution was studied and the algorithm was compared with the traditional ration-by-schedule(RBS) method. Research result shows that the improved encoding style of the NSGA-Ⅱ algorithm makes the generation distance of the solution set population converge from 600 to 30 and becomes stable after approximately 50 generations, with suitable convergence. The Pareto solution set with six solutions is generated for the multi-objective optimization model, with a 66.7% probability that the RBS method is completely dominated by the results. The average flight delay cost in the optimization results is 8.5% lower than that of the RBS method, and the average fair loss deviation coefficient is 70.6% lower. The implementation effect of the multi-objective optimization method for the space-time resources of the air route is remarkable. The fairness of each airline can be considered on the basis of reducing the total delay cost, making this an effective method for solving the problem of flight trajectory and slot resource allocation.

     

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