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Formulation | References | Criterion (comments) | Problem type |
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Integer linear programming (IP) | Lim et al. [24] | (i) Minimizing the sum of the delay penalties (ii) Minimizing the total walking distance | Theoretical |
Diepen et al. [25] | (i) Minimizing the deviation of arrival and departure time (ii) Minimizing replanning the schedule | Real case (Amsterdam Airport Schiphol) |
Diepen et al. [26] | Minimizing the deviations from the expected arrival and departure times | Real case (Amsterdam Airport Schiphol) |
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Binary integer programming | Mangoubi and Mathaisel [11]; Yan et al. [29] | Minimizing passenger walking distances | Real case (Toronto International Airport); Real case (Chiang Kai-Shek Airport) |
Vanderstraeten and Bergeron [28] | Minimizing the number off-gate event | Theoretical |
Bihr [12] | Minimizing of the total passenger distance | Theoretical |
Tang et al. [27] | Developing a gate reassignment framework and a systematic computerized tool | Real case (Taiwan International Airport) |
Prem Kumar and Bierlaire [18] | (i) Maximizing the gate rest time between two turns (ii) Minimizing the cost of towing an aircraft with a long turn (iii) Minimizing overall costs that include penalization for not assigning preferred gates to certain turns | Theoretical |
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Mixed integer linear programming (MILP) | Bolat [30] | Minimizing the range of slack times | Real case (King Khaled International Airport) |
Bolat [31] | Minimizing the variance or the range of gate idle time | Real case (King Khaled International Airport) |
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Mixed integer nonlinear programming | Li [5, 32] | Minimizing the number of gate conflicts of any two adjacent aircrafts assigned to the same gate | Real case (Continental Airlines, Houston Gorge Bush Intercontinental Airport) |
Bolat [31] | Minimizing the variance or the range of gate idle time | Real case (King Khaled International Airport) |
|
Multiple objective GAP formulations |
Hu and Di Paolo [36] | Minimize passenger walking distance, baggage transport distance, and aircraft waiting time on the apron | Theoretical |
Wei and Liu [16] | (i) Minimizing the total walking distance for passengers (ii) Minimizing the variance of gates idle times | Theoretical |
B.A.C.o.E.B. Team and A.I.C.o.E. Team [17] | (i) Minimizing walking distance (ii) Maximizing the number of gated flights (iii) Minimizing flight delays | Theoretical |
Yan and Huo [2] | (i) Minimizing passenger walking distances (ii) Minimizing the passenger waiting time | Real case (Chiang Kai-Shek Airport) |
Kaliszewski and Miroforidis [37] | Finding gate assignment efficiency which represents rational compromises between waiting time for gate and apron operations | Theoretical |
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Stochastic model | Yan and Tang [10] | Minimizing the total passenger waiting time | Real case (Taiwan International Airport) |
Genç et al. [38] | Maximizing gate duration, which is total time of the gates allocated | Theoretical and real case (Ataturk Airport of Istanbul, Turkey) |
Şeker and Noyan [9] | Minimizing the expected variance of the idle time | Theoretical |
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Quadratic assignment problem (QAP) | Drexl and Nikulin [3] | (i) Minimizing the number of ungated flights (ii) Minimizing the total passenger walking distances or connection times (iii) Maximizing the total gate assignment preferences | Theoretical |
Haghani and Chen [13] | Minimizing the total passenger walking distances | Theoretical |
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Scheduling problems |
Li [39] | (i) Maximizing the sum of the all products of the flight eigenvalue (ii) Maximizing the gate eigenvalue that the flight assigned | Theoretical |
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Quadratic mixed binary programming | Bolat [34] | Minimizing the variance of idle times | Real case (King Khaled International Airport) |
Zheng et al. [33] | Minimizing the overall variance of slack time | Real case (Beijing International Airport, China) |
Xu and Bailey [14] | Minimizing the passenger connection time | Theoretical |
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Binary quadratic programming | Ding et al. [6, 7, 35] | Minimize the number of ungated flights and the total walking distances or connection times | Theoretical |
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Clique partitioning problem (CPP) | Dorndorf et al. [8] | (i) Maximizing the total assignment preference score (ii) Minimizing the number of unassigned flights (iii) Minimizing the number of tows (iv) Maximizing the robustness of the resulting schedule | Theoretical |
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Network representation |
Maharjan and Matis [40] | Minimizing both fuel burn of aircraft and the comfort of connecting passengers | Real case (Continental Airlines at George W. Bush Intercontinental Airport in Houston (IAH)) |
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Robust optimization |
Diepen et al. [41] | Maximizing the robustness of a solution to the gate assignment problem | Real case (Amsterdam Airport Schiphol) |
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