In this paper, we focus on the resolution of Crew Pairing Optimization problem that is very visible and economically significant. Its objective is to find the best schedule, i.e., a collection of crew rotations such that each airline flight is covered by exactly one rotation and the costs are reduced to the minimum. We try to solve it with Ant Colony Optimization algorithms and Hybridizations of Ant Colony Optimization with Constraint Programming techniques. We give an illustrative example about the difficulty of pure Ant Algorithms solving strongly constrained problems. Therefore, we explore the addition of Constraint Programming mechanisms in the construction phase of the ants, so they can complete their solutions. Computational results solving some test instances of Airline Flight Crew Scheduling taken from NorthWest Airlines database are presented showing the advantages of using this kind of hybridization.
['Broderick Crawford', 'Carlos Castro', 'Eric Monfroy']
A constructive hybrid algorithm for crew pairing optimization