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