Airline Crew Pairing Optimization

Author(s):  
Laurent Alfandari ◽  
Anass Nagih
Keyword(s):  
Author(s):  
Divyam Aggarwal ◽  
Dhish Kumar Saxena ◽  
Michael Emmerich ◽  
Saaju Paulose

Author(s):  
Parames Chutima ◽  
Nicha Krisanaphan

Crew pairing is the primary cost checkpoint in airline crew scheduling. Because the crew cost comes second after the fuel cost, a substantial cost saving can be gained from effective crew pairing. In this paper, the cockpit crew pairing problem (CCPP) of a budget airline was studied. Unlike the conventional CCPP that focuses solely on the cost component, many more objectives deemed to be no less important than cost minimisation were also taken into consideration. The adaptive non-dominated sorting differential algorithm III (ANSDE III) was proposed to optimise the CCPP against many objectives simultaneously. The performance of ANSDE III was compared against the NSGA III, MOEA/D, and MODE algorithms under several Pareto optimal measurements, where ANSDE III outperformed the others in every metric.


Author(s):  
Elvin Çoban ◽  
İbrahim Muter ◽  
Duygu Taş ◽  
Ş. İlker Birbil ◽  
Kerem Bülbül ◽  
...  

2020 ◽  
Vol 1 (3) ◽  
Author(s):  
Guy Desaulniers ◽  
François Lessard ◽  
Mohammed Saddoune ◽  
François Soumis

2012 ◽  
Vol 46 (1) ◽  
pp. 39-55 ◽  
Author(s):  
Mohammed Saddoune ◽  
Guy Desaulniers ◽  
Issmail Elhallaoui ◽  
François Soumis

2013 ◽  
Vol 40 (3) ◽  
pp. 815-830 ◽  
Author(s):  
İbrahim Muter ◽  
Ş. İlker Birbil ◽  
Kerem Bülbül ◽  
Güvenç Şahin ◽  
Hüsnü Yenigün ◽  
...  

2018 ◽  
Vol 204 ◽  
pp. 02006
Author(s):  
Khusnul Novianingsih ◽  
Rieske Hadianti

The airline crew pairing problem is one of the optimization problems which classified as a NP-hard problem. Since the number of feasible pairings in flight schedules can be numerous, the exact methods will not efficient to solve the problem. We propose a heuristic method for solving crew pairing problems. Initially, we generate a feasible solution by maximizing the covered flights. Then, we improve the solution by constructing a procedure to avoid the local optimal solution. We test our method to an airline schedules. The computational results show that our method can give the optimal solution in short period of time.


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