Constraint Programming Based Column Generation for Crew Assignment
Journal of Heuristics
A new era for Crew recovery at continental airlines
Interfaces - Special issue: Franz Edelman award for achievement in operations research and the management sciences
Delta optimizes continuing-qualification-training schedules for pilots
Interfaces - Wagner prize papers
Operational airline reserve crew planning
Journal of Scheduling
Duty-period-based network model for crew rescheduling in European airlines
Journal of Scheduling
Computers and Operations Research
A Multicommodity Flow Approach to the Crew Rostering Problem
Operations Research
Selected Topics in Column Generation
Operations Research
Exact approaches for integrated aircraft fleeting and routing at TunisAir
Computational Optimization and Applications
Hi-index | 0.00 |
This paper describes the Preferential Bidding Problem solved in the airline industry to construct personalized monthly schedules for pilots and officers. This problem consists in assigning to crew members pairings, days off, annual leaves, training periods, etc., while considering a set of weighted bids that reflect individual preferences. This assignment must be done under strict seniority restrictions: the construction of a maximum-score schedule for a particular crew member must never be done at the expense of a more senior employee. This research and development project has resulted in the Preferential Bidding System that has been used at Air Canada since May 1995. The solution process is summarized as follows. For each employee, from the most senior to the most junior, a so-called residual problem is solved: given an employee and a set of unassigned pairings, the solution to an integer linear program determines the employee's maximum-score schedule while taking into account all the remaining employees. The residual problem is solved by column generation embedded in a branch-and-bound tree. Integer solutions are obtained by using very efficient cutting planes, without which it would have been impossible to solve some of these residual problems.