Title :
Genetic algorithm application on the job shop scheduling problem
Author :
Wu, C.G. ; Xing, X.L. ; Lee, H.P. ; Zhou, C.G. ; Liang, Y.C.
Author_Institution :
Coll. of Comput. Sci. & Technol., Jilin Univ., Changchun, China
Abstract :
Based on the concepts of operation template and virtual job shop, this paper attempts to solve several job shop scheduling problems with different scale and analyzes the relationship among the population size, mutation probability, the number of evolving generations and the complexity of the undertaking problem visually by using the trend chart of the fitness curves. This visual analysis could provide some referencing information for the adjustment of genetic algorithm running parameters.
Keywords :
genetic algorithms; job shop scheduling; travelling salesman problems; fitness curves; genetic algorithm; job shop scheduling problem; traveling salesman problem; visual analysis; Algorithm design and analysis; Application software; Computer science; Genetic algorithms; Genetic mutations; High performance computing; Information analysis; Job shop scheduling; Performance analysis; Processor scheduling;
Conference_Titel :
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN :
0-7803-8403-2
DOI :
10.1109/ICMLC.2004.1382144
