Tabu Search-Based Algorithm for Large Scale Crew Scheduling Problems
In this paper, the problem of finding a work schedule for airline crew members in a giventime horizon is tackled. This problem is known in the literature as Airline Crew Scheduling.The objective is to define the minimum cost schedules where each crew, associated to acombination of commercial flights...
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2005 |
| País: | México |
| Institución: | Instituto Tecnológico y de Estudios Superiores de Monterrey |
| Repositorio: | Redalyc-ITESM |
| OAI Identifier: | oai:redalyc.org:39521504 |
| Acceso en línea: | https://www.redalyc.org/articulo.oa?id=39521504 |
| Access Level: | acceso abierto |
| Palabra clave: | Administración y Contabilidad primal todual tabu search set covering metaheuristic |
| Sumario: | In this paper, the problem of finding a work schedule for airline crew members in a giventime horizon is tackled. This problem is known in the literature as Airline Crew Scheduling.The objective is to define the minimum cost schedules where each crew, associated to acombination of commercial flights or legs called pairing, is assigned to one or moreflights ensuring that the whole set of flights is covered by crew members. The CrewScheduling Problem can be modeled by using the Set Covering formulation. This paperpresents a new algorithm whose centerpiece is a primal-to-dual scheme aimed at linkingany primal solution to the dual feasible vector that best reflects the quality of the primalsolution. This new mechanism is used to intertwine a tabu search based, primal intensive,scheme with a lagrangian based, dual intensive, scheme to design a primal-dual algorithmthat progressively reduces the gap between upper and lower bound.The algorithm has been tested on benchmark problems from the literature. In this paper,results on real-world airline instances are presented: out of six well-known problems, thealgorithm is able to match the optimal solution for four of them while for the last two,whose optimal solution is not known, a new best known solution is found. |
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