MV
M.C. Vonk
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With cockpit crew costs being the second largest costs of an airline, making optimal use of the available crew is very important. The productivity of the crew is limited by the labor agreement and law regulations, which prevent the crew members from working irregularly or excessively. In this thesis we present several methods to solve the crew scheduling problem as to calculate the crew productivity based on the labor agreements and law regulations.
The crew scheduling problem is decomposed into the crew pairing problem and the crew rostering problem. A set covering approach is used to solve the traditional crew pairing problem and a matching algorithm is used to solve the crew pairing problem that arises when we allow flights being retimed. The crew rostering problem is tackled by a minimum cost flow network method and a column generation approach. All the methods are tested on a variety of flight schedules deviating in the number of night flights included. ...
The crew scheduling problem is decomposed into the crew pairing problem and the crew rostering problem. A set covering approach is used to solve the traditional crew pairing problem and a matching algorithm is used to solve the crew pairing problem that arises when we allow flights being retimed. The crew rostering problem is tackled by a minimum cost flow network method and a column generation approach. All the methods are tested on a variety of flight schedules deviating in the number of night flights included. ...
With cockpit crew costs being the second largest costs of an airline, making optimal use of the available crew is very important. The productivity of the crew is limited by the labor agreement and law regulations, which prevent the crew members from working irregularly or excessively. In this thesis we present several methods to solve the crew scheduling problem as to calculate the crew productivity based on the labor agreements and law regulations.
The crew scheduling problem is decomposed into the crew pairing problem and the crew rostering problem. A set covering approach is used to solve the traditional crew pairing problem and a matching algorithm is used to solve the crew pairing problem that arises when we allow flights being retimed. The crew rostering problem is tackled by a minimum cost flow network method and a column generation approach. All the methods are tested on a variety of flight schedules deviating in the number of night flights included.
The crew scheduling problem is decomposed into the crew pairing problem and the crew rostering problem. A set covering approach is used to solve the traditional crew pairing problem and a matching algorithm is used to solve the crew pairing problem that arises when we allow flights being retimed. The crew rostering problem is tackled by a minimum cost flow network method and a column generation approach. All the methods are tested on a variety of flight schedules deviating in the number of night flights included.