Title :
Using Ant Colony Optimization Algorithm to Solve Airline Crew Scheduling Problems
Author :
Lo, Chih-Chung ; Deng, Guang-Feng
Author_Institution :
Fo Guang Univ., Yilan
Abstract :
In this paper, an ant colony optimization (ACO) based ant crew scheduling model (ACSM) is proposed to solve airline crew scheduling problems. In the proposed ACSM, airline crew scheduling problems are first formulated as traveling salesman problems with flight graph representation. Then, the ACO algorithm is applied to search near-optimal solutions for airline crew schedules. The validity of the proposed ACSM is verified by implementing it in real study cases. The results from the implementation and evaluation confirm that the proposed ACSM is suitable for the airline crew scheduling problems with good performance.
Keywords :
graph theory; personnel; scheduling; travel industry; travelling salesman problems; airline crew scheduling problems; ant colony optimization algorithm; ant crew scheduling model; flight graph representation; traveling salesman problems; Ant colony optimization; Constraint optimization; Cost function; Feedback; Genetic algorithms; Informatics; Management information systems; Processor scheduling; Scheduling algorithm; Traveling salesman problems;
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
DOI :
10.1109/ICNC.2007.797
