Ant colony optimization-based algorithm for airline crew scheduling problem

Authors:
Guang-Feng Deng;Woo-Tsong Lin
Affiliations:
Department of Management Information Systems, National Chengchi University, 64, Sec. 2, Chihnan Rd., Wenshan Dist, Taipei 116, Taiwan, ROC;Department of Management Information Systems, National Chengchi University, 64, Sec. 2, Chihnan Rd., Wenshan Dist, Taipei 116, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Abstract

Airline crew scheduling is an NP-hard constrained combinatorial optimization problem, and an effective crew scheduling system is essential for reducing operating costs in the airline industry. Ant colony optimization algorithm (ACO) has successfully applied to solve many difficult and classical optimization problems especially on traveling salesman problems (TSP). Therefore, this paper formulated airline crew scheduling problem as Traveling Salesman Problem and then introduce ant colony optimization algorithm to solve it. Performance was evaluated by performing computational tests regarding real cases as the test problems. The results showed that ACO-based algorithm can be potential technique for airline crew scheduling.