DocumentCode :
2564346
Title :
Ant colony optimization algorithm for reactive production scheduling problem in the job shop system
Author :
Kato, E.R.R. ; Morandin, O., Jr. ; Fonseca, M.A.S.
Author_Institution :
Dept. of Comput. Sci., Fed. Univ. of Sao Carlos (UFSCar), Sao Carlos, Brazil
fYear :
2009
fDate :
11-14 Oct. 2009
Firstpage :
2199
Lastpage :
2204
Abstract :
The response time for solution scheduling problem is a import criteria of consider in real manufacturing systems where large-scale scenarios must be evaluated since as unexpected events arise. This work describes a proposed modeling and analyses for the production reactive scheduling problem in a job shop system. The scheduling problem, generally, consists in allocate the production operations with the aim of minimizing the makespan. For that, it was employed an Ant Colony Optimization algorithm applied in a matrix of the feasible solution space problem representation. In the case of a reactive system, the approach should provide good solutions in a short execution time, allowing the analysis of large scenarios in hablle times. The results of this paper were compared with the results of other approaches in small and large scenarios.
Keywords :
job shop scheduling; manufacturing systems; optimisation; ant colony optimization algorithm; job shop system; reactive production scheduling problem; reactive system; real manufacturing system; solution scheduling problem; Ant colony optimization; Artificial intelligence; Genetic algorithms; Job production systems; Job shop scheduling; Manufacturing systems; Preventive maintenance; Processor scheduling; Production systems; Scheduling algorithm; ACO; graph representation; job shop scheduling problem; reactive scheduling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on
Conference_Location :
San Antonio, TX
ISSN :
1062-922X
Print_ISBN :
978-1-4244-2793-2
Electronic_ISBN :
1062-922X
Type :
conf
DOI :
10.1109/ICSMC.2009.5345919
Filename :
5345919
Link To Document :
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