DocumentCode :
3057111
Title :
Self-adapted Hybrid Genetic Algorithm for Job Scheduling of Distributed Manufacturing System
Author :
Yang, Jingsong ; Cui, Guangcai ; Hu, Xuedan
Author_Institution :
Coll. of Comput. Sci. & Technol., Changchun Univ. of Sci. & Technol., Changchun
fYear :
2007
fDate :
14-17 Sept. 2007
Firstpage :
70
Lastpage :
73
Abstract :
An approach using the concept of self-adapted hybrid genetic algorithm (AGASA) is proposed as a powerful but simple means to optimize job scheduling in distributed manufacturing system (DMS). A directed graph model is developed to describe the characteristics of DMS. The superiority of the proposed algorithm is illustrated by computing result with pattern of GANTT graph, and the results are compared with methods of genetic algorithm and simulated annealing algorithm.
Keywords :
directed graphs; genetic algorithms; manufacturing systems; scheduling; simulated annealing; directed graph model; distributed manufacturing system; job scheduling; self-adapted hybrid genetic algorithm; simulated annealing algorithm; Batch production systems; Control systems; Flexible manufacturing systems; Flow production systems; Genetic algorithms; Job production systems; Job shop scheduling; Manufacturing systems; Processor scheduling; Workstations;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bio-Inspired Computing: Theories and Applications, 2007. BIC-TA 2007. Second International Conference on
Conference_Location :
Zhengzhou
Print_ISBN :
978-1-4244-4105-1
Electronic_ISBN :
978-1-4244-4106-8
Type :
conf
DOI :
10.1109/BICTA.2007.4806421
Filename :
4806421
Link To Document :
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