Search for Author, Title, Keyword
Evaluation of efficiency and reliability of airport processes using simulation tools
More details
Hide details
Air Force Institute of Technology, IT Logistics Support Division, ul. Księcia Bolesława 6, Warsaw, Poland
National Cyber Security Centre, ul. Rakowiecka 2, Warsaw, Poland
Warsaw University of Technology Faculty of Transport, 75 Koszykowa str. Warsaw, Poland
Publication date: 2021-12-31
Eksploatacja i Niezawodność – Maintenance and Reliability 2021;23(4):659–669
  • The genetic algorithm to evaluate the effectiveness of take-offs and landings is shown.
  • The model for assessing the implementation of airport processes is developed.
  • The proposed simulation tool reduces the landing time of aircraft.
  • The optimization of taxi routes affects the reliability of airport processes.
The purpose of this paper is to evaluate the efficiency of airport processes using simulation tools. A critical review of selected scientific studies relating to the performance of airport processes with respect to reliability, particularly within the apron, has been undertaken. The developed decision-making model evaluates the efficiency of airport processes in terms of minimizing penalties associated with aircraft landing before or after the scheduled landing time. The model takes into account, among other things, aircraft take-offs and landings and separation times between successive aircraft. In order to be able to verify the correctness of the decision-making model, a simulation tool was developed to support decision making in the implementation of airport operations based on a genetic algorithm. A novel development of the structure of a genetic algorithm as well as crossover and mutation operators adapted to the determination of aircraft movement routes on the apron is presented. The developed simulation tool was verified on real input data.
Adacher L, Flamini M, Romano E. Airport Ground Movement Problem: Minimization of Delay and Pollution Emission. IEEE Transactions on Intelligent Transportation Systems 2018; 19(12): 3830-3839,
Anagnostakis I, Clarke JP, Böhme D, Völckers U. Runway operations planning and control: Sequencing and scheduling. Journal of Aircraft 2001; 38(6): 988-996,
Anderson R, Milutinovi´c D. An approach to optimization of airport taxiway scheduling and traversal under uncertainty. Proceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering 2013; 227(2): 273-284,
Atkin JAD, Burke EK, Greenwood JS, Reeson D. Hybrid metaheuristics to aid runway scheduling at London Heathrow airport. Transportation Science 2007; 41(1): 90-106,
Bianco L, DellOlmo P, Giordani S. Scheduling models for air traffic control in terminal areas. Journal of Scheduling 2006; 9: 223-253,
Borucka A, Wiśniowski P, Mazurkiewicz D, Świderski A. Laboratory measurements of vehicle exhaust emissions in conditions reproducing real traffic. Measurement 2021; 174: 1-12,
Clare G, Richards AG. Optimization of taxiway routing and runway scheduling. IEEE Transactions on Intelligent Transportation Systems 2011; 12(4): 1000-1013,
Daniewski K, Kosicka E, Mazurkiewicz D. Analysis of the correctness of determination of the effectiveness of maintenance service actions. Management and Production Engineering Review 2018; 9(2): 20-25,
Dorndorf U, Drexl A, Nikulin Y, Pesch E. Flight gate scheduling: state-of-the-art and recent developments. Omega 2007; 35(3): 326-334,
Egbelu PJ, Tanchoko JMA. Characterization of automatic guided vehicle dispatching rules. International Journal of Production Research 1984; 22(3): 359-374,
Eun Y, Hwang I, Bang H. Optimal arrival flight sequencing and scheduling using discrete airborne delays. IEEE Transactions on Intelligent Transportation Systems 2010; 11(2): 359-373,
Garcia J, Berlanga A, Molina JM, Casar JR. Optimization of airport ground operations integrating genetic and dynamic flow management algorithms. AI Communications 2005; 18(2): 143-164.
Gołda P, Izdebski M, Szczepański E. The application of ant algorithm in the assignment problem of aircrafts to stops points on the apron. Journal of KONES Powertrain and Transport 2018; 25(1): 111-118,
Gołda P, Kowalski M, Wasser C, Dygnatowski P, Szporka A. Elements of the model positioning of aircraft on the apron. Archives of Transport 2019; 51(3): 101-108, 10.5604/01.3001.0013.6166.
Gołda P, Manerowski J. Support of aircraft taxiing operations on the apron. Journal of KONES Powertrain and Transport 2014; 21(4): 127-135,
Gołda P. Selected decision problems in the implementation of airport operations. Scientific Journal of Silesian University of Technology. Series Transport 2018; 101: 79-88,
Herrero JG, Berlanga A, Molina JM, Casar JR. Methods for operations planning in airport decision support systems. Applied Intelligence 2005; 22(3): 183-206,
Hockaday SLM, Kanafani AK. Developments in airport capacity analysis. Transportation Research 1974; 8: 171-180,
Hoshino S, Seki H, Naka Y. Pipeless batch plant with operating robots for a multiproduct production system. Distributed Autonomous Robotic Systems 1987; 4: 33-51,
Izdebski M, Jacyna M. The organization of the municipal waste collection: The decision model. Annual Set The Environment Protection 2018; 20: 919-933.
Izdebski M, Jacyna-Gołda I, Gołębiowski P, Plandor J. The Optimization Tool Supporting Supply Chain Management in the Multi-Criteria Approach. Archives of Civil Engineering 2020; 66(3): 505-524,
Izdebski M, Jacyna-Gołda I, Jakowlewa I. Planning International Transport Using the Heuristic Algorithm. Advances in Intelligent Systems and Computing 2019; 844: 229-241,
Izdebski M, Jacyna-Gołda I, Markowska K, Murawski J. Heuristic algorithms applied to the problems of servicing actors in supply chains. Archives of Transport 2017; 44(4): 25-34,
Jacyna M, Izdebski M, Szczepański E, Gołda P. The Task Assignment of Vehicles for a Production Company. Symmetry 2018; 10(11): 551,
Jacyna M, Jachimowski R, Szczepański E, Izdebski M. Road vehicle sequencing problem in a railroad intermodal terminal-simulation research. Bulletin of the Polish Academy of Sciences: Technical Sciences 2020; 68(4): 1135-1148,
Jacyna M, Semenov I. Models of vehicle service system supply under information uncertainty. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2020; 22(4): 694-704,
Jacyna-Gołda I, Izdebski M, Podviezko A. Assessment of the efficiency of assignment of vehicles to tasks in supply chains: A case-study of a municipal company. Transport 2017; 32(3): 243-251,
Jiang Y, Xu X, Zhang H, Luo Y. Taxiing route scheduling between taxiway and runway in hub airport. Mathematical Problems in Engineering 2014; 2015(1): 1-14,
Kariya Y, Yahagi H, Takehisa M, Yoshihara S, Ogata T, Hara T, Ota J. Modeling and designing aircraft taxiing patterns for a large airport. Advanced Robotics 2013; 27(14): 1059-1072,
Kowalski M, Izdebski M, Żak J, Gołda P, Manerowski J. Planning and management of aircraft maintenance using a genetic algorithm. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2021; 23(1): 143-153,
Kuchar JK, Yang LC. A review of conflict detection and resolution modeling methods. IEEE Transactions on Intelligent Transportation Systems 2000; 4(1): 179-189,
Liu Y. Study on optimization for taxiway routing arrangement based on simulation. Applied Mechanics and Materials 2011; 97-98: 550-553,
Liu YH. A genetic local search algorithm with a threshold accepting mechanism for solving the runway dependent aircraft landing problem. Optimization Letters 2011; 5(2): 229-245,
Mann GW, Hwang I. Four-dimensional aircraft taxiway conformance monitoring with constrained stochastic linear hybrid systems. Journal of Guidance, Control, and Dynamics 2012; 35(5): 1593-1604,
Montoya J, Wood Z, Rathinam S. Runway Scheduling Using Generalized Dynamic Programming. American Institute of Aeronautics and Astronautics, AIAA Guidance, Navigation, and Control Conference Portland 2011,
Mori R. Aircraft ground-taxiing model for congested airport using cellular automata. IEEE Transactions on Intelligent Transportation Systems 2013; 14(1): 180-188,
Nogueira KB, Aguiar PHC, Weigang L. Using ant algorithm to arrange taxiway sequencing in airport. International Journal of Computer Theory and Engineering 2014; 6(4): 357-361,
Nowakowski T. Reliability model of combined transportation system. [in:] Spitzer C, Schmocker U, Dang V N (ed.). Probabilistic Safety Assessment and Management. London: Springer 2004; 2012-2017,
Pitfield DE, Jerrard EA. Monte Carlo comes Rome: a note on the estimation of unconstrained runway capacity at Rome fiumucino international airport. Journal of Air Transport Management 1999; 5: 185-192,
Rathinam S, Montoya J, Jung Y. An optimization model for reducing aircraft taxi times at the Dallas Fort Worth International Airport. 26th International Congress of the Aeronautical Sciences 2008.
Ravizza S, Atkin JAD, Maathuis MH, Burke EK. A combined statistical approach and ground movement model for improving taxi time estimations at airports. Journal of the Operational Research Society 2013; 64(9): 1347-1360,
Rodríguez-Sanz Á , Fernández BR, Comendador FG, Valdés RA, García JMC, Bagamanova M. Operational Reliability of the Airport System: Monitoring and Forecasting. Transportation Research Procedia 2018; 33: 363-370,
Roling PC, Visser HG. Optimal airport surface traffic planning using mixed-integer linear programming. International Journal of Aerospace Engineering 2008; 2008(1): 1-11,
Siddiqee W. A mathematical model for predicting the number of potential conflict situations at intersecting air routes. Transportation Science 1973; 7: 158-167,
Solveling G, Solak S, Clarke JP, Johnson E. Runaway operations optimization in the presence of uncertainties. Journal of Guidance Control, and Dynamics 2011; 34(5): 1373-1381,
Szaciłło L, Szczepański E, Izdebski M, Jacyna M. Risk assesment for rail freight transport operations. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2021; 23(3): 476-488,
Turskis Z, Antuchevičienė J, Keršulienė V, Gaidukas G. Hybrid Group MCDM Model to Select the Most Effective Alternative of the Second Runway of the Airport. Symmetry 2019; 11(6):792.
Wasiak M, Jacyna-Gołda I, Markowska K, Jachimowski R, Kłodawski M, Izdebski M. The use of a supply chain configuration model to assess the reliability of logistics processes. Eksploatacja i Niezawodnosc – Maintenance and Reliability 2019; 21 (3): 367–374,
Zieja M, Smoliński H, Gołda P. Information systems as a tool for supporting the management of aircraft flight safety. Archives of Transport 2015; 36(4): 67-76,
The Use of the Ant Algorithm in the Model of Safety Management of the Traffic Organization At the Apron
Mariusz Izdebski, Paweł Gołda, Tomasz Zawisza
Journal of KONBiN
Method for Calculating the Required Number of Transport Vehicles Supplying Aviation Fuel to Aircraft during Combat Tasks
Jarosław Ziółkowski, Józef Żurek, Jerzy Małachowski, Mateusz Oszczypała, Joanna Szkutnik-Rogoż
A method for evaluating and upgrading systems with parallel structures with forced redundancy
Edward Michlowicz, Jerzy Wojciechowski
Eksploatacja i Niezawodnosc - Maintenance and Reliability
Energy Efficiency of Transport Tasks Performed by the Air SAR System in the Baltic Sea: Case Study
Jerzy Fiuk, Norbert Chamier-Gliszczynski, Marianna Jacyna, Mariusz Izdebski
Advanced Solutions and Practical Applications in Road Traffic Engineering
Mariusz Izdebski, Paweł Gołda, Tomasz Zawisza
Modelling the Operation Process of Light Utility Vehicles in Transport Systems Using Monte Carlo Simulation and Semi-Markov Approach
Mateusz Oszczypała, Jarosław Ziółkowski, Jerzy Małachowski