A multi-objective evolutionary approach to aircraft landing scheduling problems

Ke Tang; Zai Wang; Xianbin Cao; Jun Zhang

doi:10.1109/CEC.2008.4631292

A multi-objective evolutionary approach to aircraft landing scheduling problems

Ke Tang^*, Zai Wang, Xianbin Cao, Jun Zhang

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

25 Citations (Scopus)

Abstract

Scheduling aircraft landings has been a complex and challenging problem in air traffic control for long time. In this paper, we propose to solve the aircraft landing scheduling problem (ALSP) using multi-objective evolutionary algorithms (MOEAs). Specifically, we consider simultaneously minimizing the total scheduled time of arrival and the total cost, and formulate the ALSP as a 2-objective optimization problem. A MOEA named Multi-Objective Neighborhood Search Differential Evolution (MONSDE) is applied to solve the 2-objective ALSP. Besides, a ranking scheme named non-dominated average ranking is also proposed to determine the optimal landing sequence. Advantages of our approaches are demonstrated on two example scenarios.

Original language	English
Title of host publication	2008 IEEE Congress on Evolutionary Computation, CEC 2008
Pages	3650-3656
Number of pages	7
DOIs	https://doi.org/10.1109/CEC.2008.4631292
Publication status	Published - 2008
Externally published	Yes
Event	2008 IEEE Congress on Evolutionary Computation, CEC 2008 - Hong Kong, China Duration: 1 Jun 2008 → 6 Jun 2008

Publication series

Name	2008 IEEE Congress on Evolutionary Computation, CEC 2008

Conference

Conference	2008 IEEE Congress on Evolutionary Computation, CEC 2008
Country/Territory	China
City	Hong Kong
Period	1/06/08 → 6/06/08

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10.1109/CEC.2008.4631292

Cite this

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title = "A multi-objective evolutionary approach to aircraft landing scheduling problems",

abstract = "Scheduling aircraft landings has been a complex and challenging problem in air traffic control for long time. In this paper, we propose to solve the aircraft landing scheduling problem (ALSP) using multi-objective evolutionary algorithms (MOEAs). Specifically, we consider simultaneously minimizing the total scheduled time of arrival and the total cost, and formulate the ALSP as a 2-objective optimization problem. A MOEA named Multi-Objective Neighborhood Search Differential Evolution (MONSDE) is applied to solve the 2-objective ALSP. Besides, a ranking scheme named non-dominated average ranking is also proposed to determine the optimal landing sequence. Advantages of our approaches are demonstrated on two example scenarios.",

author = "Ke Tang and Zai Wang and Xianbin Cao and Jun Zhang",

year = "2008",

doi = "10.1109/CEC.2008.4631292",

language = "English",

isbn = "9781424418237",

series = "2008 IEEE Congress on Evolutionary Computation, CEC 2008",

pages = "3650--3656",

booktitle = "2008 IEEE Congress on Evolutionary Computation, CEC 2008",

note = "2008 IEEE Congress on Evolutionary Computation, CEC 2008 ; Conference date: 01-06-2008 Through 06-06-2008",

}

Tang, K, Wang, Z, Cao, X & Zhang, J 2008, A multi-objective evolutionary approach to aircraft landing scheduling problems. in 2008 IEEE Congress on Evolutionary Computation, CEC 2008., 4631292, 2008 IEEE Congress on Evolutionary Computation, CEC 2008, pp. 3650-3656, 2008 IEEE Congress on Evolutionary Computation, CEC 2008, Hong Kong, China, 1/06/08. https://doi.org/10.1109/CEC.2008.4631292

A multi-objective evolutionary approach to aircraft landing scheduling problems. / Tang, Ke; Wang, Zai; Cao, Xianbin et al.
2008 IEEE Congress on Evolutionary Computation, CEC 2008. 2008. p. 3650-3656 4631292 (2008 IEEE Congress on Evolutionary Computation, CEC 2008).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - Scheduling aircraft landings has been a complex and challenging problem in air traffic control for long time. In this paper, we propose to solve the aircraft landing scheduling problem (ALSP) using multi-objective evolutionary algorithms (MOEAs). Specifically, we consider simultaneously minimizing the total scheduled time of arrival and the total cost, and formulate the ALSP as a 2-objective optimization problem. A MOEA named Multi-Objective Neighborhood Search Differential Evolution (MONSDE) is applied to solve the 2-objective ALSP. Besides, a ranking scheme named non-dominated average ranking is also proposed to determine the optimal landing sequence. Advantages of our approaches are demonstrated on two example scenarios.

AB - Scheduling aircraft landings has been a complex and challenging problem in air traffic control for long time. In this paper, we propose to solve the aircraft landing scheduling problem (ALSP) using multi-objective evolutionary algorithms (MOEAs). Specifically, we consider simultaneously minimizing the total scheduled time of arrival and the total cost, and formulate the ALSP as a 2-objective optimization problem. A MOEA named Multi-Objective Neighborhood Search Differential Evolution (MONSDE) is applied to solve the 2-objective ALSP. Besides, a ranking scheme named non-dominated average ranking is also proposed to determine the optimal landing sequence. Advantages of our approaches are demonstrated on two example scenarios.

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A multi-objective evolutionary approach to aircraft landing scheduling problems

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