DocumentCode :
2055743
Title :
Static task graph scheduling using learner Genetic Algorithm
Author :
Ghader, Habib Motee ; Fakhr, Kambiz ; Javadi, Mahmood ; Bakhshzadeh, Gisou
Author_Institution :
Comput. Eng. Dept., Islamic Azad Univ. - Tabriz Branch, Tabriz, Iran
fYear :
2010
fDate :
7-10 Dec. 2010
Firstpage :
357
Lastpage :
362
Abstract :
Task graph scheduling is one of the NP-Hard problems. So many classic and non-classic methods are proposed for solution of this problem. One of the crucial methods that, applied for solving this problem is Genetic Algorithm. In this paper we propose a new algorithm that named Learner Genetic Algorithm (LGA). Our proposed algorithm based on Genetic Algorithm, but in new proposed algorithm the Learning Process is attached for Genetic Algorithm. The scheduling resulted from applying our proposed algorithm to some benchmark task graphs are compared with the existing ones.
Keywords :
computational complexity; genetic algorithms; graph theory; learning (artificial intelligence); processor scheduling; NP-hard problem; genetic algorithm; learning process; multiprocessor system; task graph scheduling; Algorithm design and analysis; Automata; Biological cells; Learning automata; Optimal scheduling; Processor scheduling; Program processors; Genetic Algorithm; Learning Automata; Multiprocessor Systems; Scheduling; Task Graph;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Soft Computing and Pattern Recognition (SoCPaR), 2010 International Conference of
Conference_Location :
Paris
Print_ISBN :
978-1-4244-7897-2
Type :
conf
DOI :
10.1109/SOCPAR.2010.5686731
Filename :
5686731
Link To Document :
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