Title :
GraGA: a graph based genetic algorithm for airline crew scheduling
Author :
Ozdemir, H. Timucin ; Mohan, Chilukuri K.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Syracuse Univ., NY, USA
Abstract :
Crew scheduling is an NP-hard constrained combinatorial optimization problem, which is very important for the airline industry. We propose a genetic algorithm, GraGA, to solve this problem. A new graph based representation utilizes memory effectively, and provides a framework in which we can easily develop various genetic operators
Keywords :
aerospace computing; genetic algorithms; scheduling; travel industry; GraGA; NP-hard constrained combinatorial optimization problem; airline crew scheduling; airline industry; graph based genetic algorithm; graph based representation; Biological cells; Constraint optimization; Cost function; Dynamic scheduling; FAA; Fuels; Genetic algorithms; Genetic mutations; Job shop scheduling; Processor scheduling;
Conference_Titel :
Tools with Artificial Intelligence, 1999. Proceedings. 11th IEEE International Conference on
Conference_Location :
Chicago, IL
Print_ISBN :
0-7695-0456-6
DOI :
10.1109/TAI.1999.809761
