Abstract
Crew pairing problem (CPP) deals with generating crew pairings due to law and restrictions and selecting a set of crew pairings with minimal cost that covers all the flight legs. In the literature, CPP can be formulated as set covering problem (SCP) which is an NP-hard problem. In this study, we present a hybrid approach (HA) that combines genetic based heuristic (GBH) and integer programming (IP). GBH generates a reduced search space including legal crew pairings with high quality. IP solver is then used to solve set covering problem which selects the minimal cost pairings among solutions in the reduced search space. The effectiveness of the proposed HA is comparatively investigated using a random search algorithm (RSA) and column generation technique (CG). Computational results show that HA is more effective than RSA and CG in terms of the computation cost of solution quality.
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