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A Bi-Objective Constrained Robust Gate Assignment Problem: Formulation, Instances and Algorithm.

Publication ,  Journal Article
Cai, X; Sun, W; Misir, M; Tan, KC; Li, X; Xu, T; Fan, Z
Published in: IEEE transactions on cybernetics
September 2021

The gate assignment problem (GAP) aims at assigning gates to aircraft considering operational efficiency of airport and satisfaction of passengers. Unlike the existing works, we model the GAP as a bi-objective constrained optimization problem. The total walking distance of passengers and the total robust cost of the gate assignment are the two objectives to be optimized, while satisfying the constraints regarding the limited number of flights assigned to apron, as well as three types of compatibility. A set of real instances is then constructed based on the data obtained from the Baiyun airport (CAN) in Guangzhou, China. A two-phase large neighborhood search (2PLNS) is proposed, which accommodates a greedy and stochastic strategy (GSS) for the large neighborhood search; both to speed up its convergence and to avoid local optima. The empirical analysis and results on both the synthetic instances and the constructed real-world instances show a better performance for the proposed 2PLNS as compared to many state-of-the-art algorithms in literature. An efficient way of choosing the tradeoff from a large number of nondominated solutions is also discussed in this article.

Duke Scholars

Published In

IEEE transactions on cybernetics

DOI

EISSN

2168-2275

ISSN

2168-2267

Publication Date

September 2021

Volume

51

Issue

9

Start / End Page

4488 / 4500

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 4611 Machine learning
  • 4603 Computer vision and multimedia computation
  • 4602 Artificial intelligence
  • 0906 Electrical and Electronic Engineering
  • 0801 Artificial Intelligence and Image Processing
  • 0102 Applied Mathematics
 

Citation

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Cai, X., Sun, W., Misir, M., Tan, K. C., Li, X., Xu, T., & Fan, Z. (2021). A Bi-Objective Constrained Robust Gate Assignment Problem: Formulation, Instances and Algorithm. IEEE Transactions on Cybernetics, 51(9), 4488–4500. https://doi.org/10.1109/tcyb.2019.2956974
Cai, Xinye, Wenxue Sun, Mustafa Misir, Kay Chen Tan, Xiaoping Li, Tao Xu, and Zhun Fan. “A Bi-Objective Constrained Robust Gate Assignment Problem: Formulation, Instances and Algorithm.IEEE Transactions on Cybernetics 51, no. 9 (September 2021): 4488–4500. https://doi.org/10.1109/tcyb.2019.2956974.
Cai X, Sun W, Misir M, Tan KC, Li X, Xu T, et al. A Bi-Objective Constrained Robust Gate Assignment Problem: Formulation, Instances and Algorithm. IEEE transactions on cybernetics. 2021 Sep;51(9):4488–500.
Cai, Xinye, et al. “A Bi-Objective Constrained Robust Gate Assignment Problem: Formulation, Instances and Algorithm.IEEE Transactions on Cybernetics, vol. 51, no. 9, Sept. 2021, pp. 4488–500. Epmc, doi:10.1109/tcyb.2019.2956974.
Cai X, Sun W, Misir M, Tan KC, Li X, Xu T, Fan Z. A Bi-Objective Constrained Robust Gate Assignment Problem: Formulation, Instances and Algorithm. IEEE transactions on cybernetics. 2021 Sep;51(9):4488–4500.

Published In

IEEE transactions on cybernetics

DOI

EISSN

2168-2275

ISSN

2168-2267

Publication Date

September 2021

Volume

51

Issue

9

Start / End Page

4488 / 4500

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 4611 Machine learning
  • 4603 Computer vision and multimedia computation
  • 4602 Artificial intelligence
  • 0906 Electrical and Electronic Engineering
  • 0801 Artificial Intelligence and Image Processing
  • 0102 Applied Mathematics