A constructive hybrid algorithm for crew pairing optimization

Broderick Crawford, Carlos Castro, Eric Monfroy

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

6 Citas (Scopus)


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.

Idioma originalInglés
Título de la publicación alojadaArtificial Intelligence
Subtítulo de la publicación alojadaMethodology, Systems, and Applications - 12th International Conference, AIMSA 2006, Proceedings
EditorialSpringer Verlag
Número de páginas11
ISBN (versión impresa)3540409300, 9783540409304
EstadoPublicada - 2006
Evento12th International Conference on Artificial Intelligence: Methodology, Systems, and Applications, AIMSA 2006 - Varna, Bulgaria
Duración: 12 sep. 200615 sep. 2006

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen4183 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349


Conferencia12th International Conference on Artificial Intelligence: Methodology, Systems, and Applications, AIMSA 2006


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