An Integrated Bi-Objective Mathematical Model for Minimizing Take-off Delay and Passenger Dissatisfaction
Subject Areas : Cultural and Language Studies
Razieh
Larizadeh
1
(Department of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran)
Reza
Ramezanian
2
(Department of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran)
Keywords: NSGA-II, Airport planning, Airport scheduling, Flight delay, NWSM, MOGWO,
Abstract :
As air transportation has increased in recent years, it is necessary for airport planners to optimally manage aircraft ground traffic on stands, taxiways and runways in order to minimize flight delay and passenger dissatisfaction. A closer look at the literature in this area indicates that most studies have merely focused on one of these resources which in a macroscopic level may result in aircrafts’ collision and ground traffic at the airport. In this paper, a new bi-objective Mixed-Integer Linear Programming (MILP) model is developed to help airport management to integrate Gate Assignment Problem (GAP) and Runway Scheduling Problem (RSP) considering taxiing operation for departing flights. The proposed model aims to help airport planners to 1) minimize any deviation from preferred schedule and 2) minimize transit passengers’ walking distance. Due to the complexity of the research problem, a Normalized Weighted Sum Method (NWSM) is applied to solve small-sized problems and two meta-heuristics, namely NSGA-II and MOGWO, are used for large-scale instances to generate Pareto optimal solutions. The performance of these algorithms is assessed by well-known coverage and convergence measures. Based on the most criteria, the results indicate that MOGWO outperforms NSGA-II.
Aktel, A., Yagmahan, B., Özcan, T., Yenisey, M.M. and Sansarcı, E. (2017). The comparison of the metaheuristic algorithms performances on airport gate assignment problem. Transportation Research Procedia, 22, 469-478.
Atkin, J.A., Burke, E.K., Greenwood, J.S., and Reeson, D. (2007). Hybrid metaheuristics to aid runway scheduling at London Heathrow airport. Transportation Science, 41(1), 90-106.
Bennell, J.A., Mesgarpour, M., and Potts, C.N. (2011). Airport runway scheduling. 4OR, 9(2), 115.
Bennell, J.A., Mesgarpour, M., and Potts, C.N. (2017). Dynamic scheduling of aircraft landings. European Journal of Operational Research, 258(1), 315-327.
Clare, G., and Richards, A.G. (2011). Optimization of taxiway routing and runway scheduling. IEEE Transactions on Intelligent Transportation Systems, 12(4), 1000-1013.
Coello, C.A.C., Pulido, G.T., and Lechuga, M.S. (2004). Handling multiple objectives with particle swarm optimization. IEEE Transactions on evolutionary computation, 8(3), 256-279.
Daş, G.S., Gzara, F., and Stützle, T. (2020). A review on airport gate assignment problems: Single versus multi objective approaches. Omega, 92, 102146.
Deb, K., Pratap, A., Agarwal, S., and Meyarivan, T.A.M.T. (2002). A fast and elitist multi objective genetic algorithm: NSGA-II. IEEE transactions on evolutionary computation, 6(2), 182-197.
Guépet, J., Briant, O., Gayon, J.P., and Acuna-Agost, R. (2016). The aircraft ground routing problem: Analysis of industry punctuality indicators in a sustainable perspective. European Journal of Operational Research, 248(3), 827-839.
Hwang, C.L., and Masud, A.S.M. (2012). Multiple objective decision making—methods and applications: a state-of-the-art survey. Springer Science & Business Media, 164.
Khakzar Bafruei, M., Khatibi, S., & Rahmani, M. (2018). A Bi-Objective Airport Gate Scheduling with Controllable Processing Times Using Harmony Search and NSGA-II Algorithms. Journal of Optimization in Industrial Engineering, 11(1), 77-90.
Kim, I.Y., and de Weck, O.L. (2005). Adaptive weighted-sum method for bi-objective optimization: Pareto front generation. Structural and multidisciplinary optimization, 29(2), 149-158.
Lee, J., Im, H., Kim, K. H., Xi, S., & Lee, C. (2016). AIRPORT GATE ASSIGNMENT FOR IMPROVING TERMINALS'INTERNAL GATE EFFICIENCY. International Journal of Industrial Engineering, 23(6).
Lieder, A., and Stolletz, R. (2016). Scheduling aircraft take-offs and landings on interdependent and heterogeneous runways. Transportation research part E: logistics and transportation review, 88, 167-188.
Maadanpour Safari, F., Etebari, F., & Pourghader Chobar, A. (2021). Modelling and optimization of a tri-objective Transportation-Location-Routing Problem considering route reliability: using MOGWO, MOPSO, MOWCA and NSGA-II. Journal of Optimization in Industrial Engineering, 14(2), 99-114.
Messaoud, M. B., Ghedira, K., & Harizi, R. (2017, October). The multiple runway aircraft landing problem: A case study for tunis carthage airport. In 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 2802-2807). IEEE.
Mirjalili, S., Mirjalili, S.M., and Lewis, A. (2014). Grey wolf optimizer. Advances in engineering software, 69, 46-61.
Mirjalili, S., Saremi, S., Mirjalili, S.M., and Coelho, L.D.S. (2016). Multi-objective grey wolf optimizer: a novel algorithm for multi-criterion optimization. Expert Systems with Applications, 47, 106-119.
Nourmohammadzadeh, A. (2012). A comprehensive multi-objective mathematical model for the problem of landing and takeoff scheduling and gate assignment at the airport. Master Dissertation, Tehran University (UT), Tehran, Iran.
Organisation de l'aviation civile internationale. (2004). Advanced Surface Movement Guidance and Control Systems (A-SMGCS) Manual. ICAO.
Pohl, M., Kolisch, R., & Schiffer, M. (2020). Runway scheduling during winter operations. Omega, 102325.
Ryu, J.H., Kim, S., and Wan, H. (2009). Pareto front approximation with adaptive weighted sum method in multi objective simulation optimization. In Proceedings of the 2009 Winter Simulation Conference (WSC), 623-633.
Samà, M., D'Ariano, A., Corman, F., and Pacciarelli, D. (2018). Coordination of scheduling decisions in the management of airport airspace and taxiway operations. Transportation Research Part A: Policy and Practice, 114, 398-411.
Sierra, M.R., and Coello, C.A.C. (2005). Improving PSO-based multi-objective optimization using crowding, mutation and ∈-dominance. In International conference on evolutionary multi-criterion optimization, Springer, Berlin, Heidelberg, 505-519.
Yu, C. (2015). Airport ground services optimization with gate assignment and reassignment. Ph.D. Dissertation, The university of Hong Kong, Hong Kong.
Yu, C., Zhang, D., and Lau, H.H. (2017). A heuristic approach for solving an integrated gate reassignment and taxi scheduling problem. Journal of Air Transport Management, 62, 189-196.
Zitzler, E., & Thiele, L. (1999). Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach. IEEE transactions on Evolutionary Computation, 3(4), 257-271.