An integrated crew scheduling problem considering reserve crew in air transportation: Ant colony optimization algorithm
Subject Areas : Business and MarketingSaeed Saemi 1 , Alireza Rashidi Komijan 2 , Reza Tavakkoli-Moghaddam 3 , Mohammad Fallah 4
1 - Department of Industrial Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran
2 - Islamic Azad University, Firoozkoh Branch
3 - North Karegar Street
School of Industrial Engineering, College of Engineering, University of Tehran
4 - Department of Industrial Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran
Keywords:
Abstract :
Aggarwal, D., Saxena, D. K., Emmerich, M., & Paulose, S.S (2018). On large-scale airline crew pairing generation. In: Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence (SSCI), Bangalore, India, 18-21, 593-600.
AhmadBeygi, S., Cohn, A., & Weir, M. (2009). An integer programming approach to generating airline crew pairings. Computers & Operations Research, 36(4), 1284-1298.
Aydemir-Karadag, A., Dengiz, B., & Bolat, A. (2013). Crew pairing optimization based on hybrid approaches. Computers & Industrial Engineering, 65(1), 87-96.
Azadeh, A., Farahani, M. H., Eivazy, H., Nazari-Shirkouhi, S., & Asadipour, G. (2013). A hybrid meta-heuristic algorithm for optimization of crew scheduling. Applied Soft Computing, 13(1), 158-164.
Barnhart, C. (2008). Airline scheduling: Accomplishments, opportunities and challenges. In International Conference on Integration of Artificial Intelligence (AI) and Operations Research (OR) Techniques in Constraint Programming (pp. 1-1). Springer, Berlin, Heidelberg.
Bayliss, C., De Maere, G., Atkin, J. A., & Paelinck, M. (2017). A simulation scenario based mixed integer programming approach to airline reserve crew scheduling under uncertainty. Annals of Operations Research, 252(2), 335-363.
Bayliss, C., De Maere, G., Atkin, J., & Paelinck, M. (2012). Probabilistic airline reserve crew scheduling model. In D. Delling & L. Liberti (Eds.), In: Proceedings of the 12th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS). Ljubljana, Slovenia, 13 September 2012. 132–143.
Bazargan, M. (2016). Airline operations and scheduling. London: Routledge.
De Armas, J., Cadarso, L., Juan, A. A., & Faulin, J. (2017). A multi-start randomized heuristic for real-life crew rostering problems in airlines with work-balancing goals. Annals of Operations Research, 258(2), 825-848.
Dehnavi-Arani, S., Sabaghian, A., & Fazli, M. (2019). A Job shop scheduling and location of battery charging storage for the automated guided vehicles (AGVs). Journal of Optimization in Industrial Engineering, 12(2), 121-129.
Deng, G. F., & Lin, W. T. (2011). Ant colony optimization-based algorithm for airline crew scheduling problem. Expert Systems with Applications, 38(5), 5787-5793.
Doi, T., Nishi, T., & Voß, S. (2018). Two-level decomposition-based matheuristic for airline crew rostering problems with fair working time. European Journal of Operational Research, 267(2), 428-438.
Dorigo, M., Maniezzo, V., & Colorni, A. (1996). Ant system: optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 26(1), 29-41.
Enayati, M., Asadi-Gangraj, E., & Paydar, M. M. (2021). Scheduling on flexible flow shop with cost-related objective function considering outsourcing options. Journal of Optimization in Industrial Engineering, 14(2), 53-72.
Erdoğan, G., Haouari, M., Matoglu, M. Ö., & Özener, O. Ö. (2015). Solving a large-scale crew pairing problem. Journal of the Operational Research Society, 66(10), 1742-1754.
Hadianti, R., Novianingsih, K., Uttunggadewa, S., Sidarto, K. A., Sumarti, N., & Soewono, E. (2013). Optimization model for an airline crew rostering problem: Case of Garuda Indonesia. Journal of Mathematical and Fundamental Sciences. 45: 218-234.
Haouari, M., Zeghal Mansour, F., & Sherali, H. D. (2019). A new compact formulation for the daily crew pairing problem. Transportation Science, 53(3), 811-828.
Kasirzadeh, A., Saddoune, M., & Soumis, F. (2017). Airline crew scheduling: models, algorithms, and data sets. EURO Journal on Transportation and Logistics, 6(2), 111-137.
Klabjan, D., Johnson, E. L., Nemhauser, G. L., Gelman, E., & Ramaswamy, S. (2001). Solving large airline crew scheduling problems: Random pairing generation and strong branching. Computational Optimization and Applications, 20(1), 73-91.
Kohl, N., & Karisch, S. E. (2004). Airline crew rostering: Problem types, modeling, and optimization. Annals of Operations Research, 127(1), 223-257.
Maenhout, B., & Vanhoucke, M. (2010). A hybrid scatter search heuristic for personalized crew rostering in the airline industry. European Journal of Operational Research, 206(1), 155-167.
Ozdemir, H. T., & Mohan, C. K. (2001). Flight graph based genetic algorithm for crew scheduling in airlines. Information Sciences, 133(4), 165-173.
Quesnel, F., Desaulniers, G., & Soumis, F. (2017). A new heuristic branching scheme for the crew pairing problem with base constraints. Computers & Operations Research, 80, 159-172.
Quesnel, F., Desaulniers, G., & Soumis, F. (2020). Improving air crew rostering by considering crew preferences in the crew pairing problem. Transportation Science, 54(1), 97-114.
Rashidi Komijan, A., Ghasemi, P., Khalili-Damghani, K., & HashemiYazdi, F. (2021a). A new school bus routing problem considering gender separation, special students and mix loading: a genetic algorithm approach. Journal of Optimization in Industrial Engineering, 14(2), 23-39.
Rashidi Komijan, A., Tavakkoli-Moghaddam, R., & Dalil, S. A. (2021b). A mathematical model for an integrated airline fleet assignment and crew scheduling problem solved by vibration damping optimization. Scientia Iranica, 28(2), 970-984.
Saddoune, M., Desaulniers, G., Elhallaoui, I., & Soumis, F. (2012). Integrated airline crew pairing and crew assignment by dynamic constraint aggregation. Transportation Science, 46(1), 39-55.
Saemi, S., Komijan, A. R., Tavakkoli-Moghaddam, R., & Fallah, M. (2021). A new mathematical model to cover crew pairing and rostering problems simultaneously. Journal of Engineering Research, 9(2).
Saemi, S., Komijan, A. R., Tavakkoli-Moghaddam, R., & Fallah, M. (2022). Solving an integrated mathematical model for crew pairing and rostering problems by an ant colony optimisation algorithm. European Journal of Industrial Engineering, 16(2), 215-240.
Santosa, B., Sunarto, A., & Rahman, A. (2010). Using differential evolution method to solve crew rostering problem. Applied Mathematics. 1: 316-325.
Shafipour-Omrani, B., Komijan, A. R., Sadjadi, S. J., Khalili-Damghani, K., & Ghezavati, V. (2021). "A flexible mathematical model for crew pairing optimization to generate n-day pairings considering the risk of COVID-19: a real case study", Kybernetes, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/K-02-2021-0127.
Shebalov, S., & Klabjan, D. (2006). Robust airline crew pairing: Move-up crews. Transportation science, 40(3), 300-312.
Sohoni, M. G., Johnson, E. L., & Bailey, T. G. (2006). Operational airline reserve crew planning. Journal of Scheduling, 9(3), 203-221.
Taguchi, G., Chowdhury, S., & Wu, Y. (2005). Taguchi's quality engineering handbook. Wiley.
Zeren, B., & Ozkol, I. (2012). An improved genetic algorithm for crew pairing optimization. Journal of Intelligent Learning Systems and Applications. 4: 70-80.
Zeren, B., & Özkol, I. (2016). A novel column generation strategy for large scale airline crew pairing problems. Expert Systems with Applications, 55, 133-144.