Title of article :
Ant colony optimization-based algorithm for airline crew scheduling problem
Author/Authors :
Deng، نويسنده , , Guang-Feng and Lin، نويسنده , , Woo-Tsong، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2011
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.
Keywords :
Ant Colony Optimization (ACO) , swarm intelligence , Combinatorial optimization problem , Airline crew scheduling
Journal title :
Expert Systems with Applications
Journal title :
Expert Systems with Applications