A bi-objective constrained robust gate assignment problem: formulation, instances and algorithm

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dc.authoridMustafa Mısır / 0000-0002-6885-6775en_US
dc.authorscopusidMustafa Mısır / 36458858100en_US
dc.authorwosidMustafa Mısır / A-6739-2010en_US
dc.contributor.authorCai, Xinye
dc.contributor.authorSun, Wenxue
dc.contributor.authorMısır, Mustafa
dc.contributor.authorTan, Kay Chen
dc.contributor.authorLi, Xiaoping
dc.contributor.authorXu, Tao
dc.contributor.authorFan, Zhun
dc.date.accessioned2021-09-24T06:05:16Z
dc.date.available2021-09-24T06:05:16Z
dc.date.issued2021en_US
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.description.abstractThe 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.en_US
dc.identifier.citationCai, 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.en_US
dc.identifier.doi10.1109/TCYB.2019.2956974en_US
dc.identifier.endpage4500en_US
dc.identifier.issn2168-2267en_US
dc.identifier.issn2168-2275en_US
dc.identifier.issue9en_US
dc.identifier.pmid31899446en_US
dc.identifier.scopus2-s2.0-85100255118en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage4488en_US
dc.identifier.urihttps://doi.org/10.1109/TCYB.2019.2956974
dc.identifier.urihttps://hdl.handle.net/20.500.12713/2101
dc.identifier.volume51en_US
dc.identifier.wosWOS:000696078900016en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakPubMeden_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorMısır, Mustafa
dc.language.isoenen_US
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCen_US
dc.relation.ispartofIEEE TRANSACTIONS ON CYBERNETICSen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectLogic Gatesen_US
dc.subjectOptimizationen_US
dc.subjectAircraften_US
dc.subjectAirportsen_US
dc.subjectAtmospheric Modelingen_US
dc.subjectRobustnessen_US
dc.subjectLegged Locomotionen_US
dc.subjectBi-Objective Optimizationen_US
dc.subjectLarge Neighborhood Search (LNS)en_US
dc.subjectPareto Local Search (PLS)en_US
dc.subjectRobust Gate Assignmenten_US
dc.subjectSolutions of Interesten_US
dc.titleA bi-objective constrained robust gate assignment problem: formulation, instances and algorithmen_US
dc.typeConference Objecten_US

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