Title :
Using Matrix-Coded Genetic Algorithm for Solving the Flexible Job-Shop Scheduling
Author_Institution :
Sch. of Manage. Sci. & Eng., Zhengzhou Inst. of Aeronaut. Ind. Manage., Zhengzhou, China
Abstract :
A matrix-coded genetic algorithm is proposed for solving the flexible job shop scheduling problem (FJSP). Novel strategies have been incorporated into crossover operator and mutation operator to assist the matrix-coded genetic algorithm to perform well. The matrix-coded genetic algorithm is a direct-viewing and easy to operate, a set of benchmark taken from the literature are tested. The computation results show the matrix-coded genetic algorithm is effective.
Keywords :
genetic algorithms; job shop scheduling; crossover operator; flexible job shop scheduling; matrix-coded genetic algorithm; mutation operator; Biological cells; Encoding; Gallium; Genetic algorithms; Indexes; Job shop scheduling;
Conference_Titel :
Computational Intelligence and Software Engineering (CiSE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5391-7
Electronic_ISBN :
978-1-4244-5392-4
DOI :
10.1109/CISE.2010.5676732
