Solving the airline crew recovery problem by a genetic algorithm with local improvement

Solving the airline crew recovery problem by a genetic algorithm with local improvement

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Article ID: iaor20073235
Country: Greece
Volume: 5
Issue: 2
Publication Date: May 2005
Journal: Operational Research - An International Journal
Authors: , ,
Keywords: heuristics: genetic algorithms, transportation: air
Abstract:

Within the complex and dynamic environment of the airline industry, any disturbance to normal operations has dramatic impact, and usually imposes high additional costs. Because of irregular events during day-to-day operations, airline crew schedules are rarely operated as planned in practice. Therefore, disrupted schedules should be recovered with as small changes as possible. In this article, we propose a genetic algorithm (GA) based approach, in which disrupted flights are reassigned within an evolutionary process. Because of the slow convergence rate achieved by conventional GA, a special local improvement procedure is applied in this approach. Computational results are reported for several disruption scenarios on real-life instances from a medium-sized European airline.

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