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Task Scheduling using Parallel Genetic Simulated Annealing Algorithm

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3 Author(s)
Shijue Zheng ; Department of Computer Science, Hua Zhong Normal University, Wuhan 430079, China. e-mail: ; Wanneng Shu ; Li Gao

Task scheduling is a NP-hard problem and is an integral part of parallel and distributed computing. This paper combined with the advantages of genetic algorithm and simulated annealing, brings forward a parallel genetic simulated annealing algorithm and applied to solve task scheduling in grid computing. It first generates a new group of individuals through genetic operation such as reproduction, crossover, mutation, etc, and than simulated anneals independently all the generated individuals respectively. When the temperature in the process of cooling no longer falls, the result is the optimal solution on the whole. From the analysis and experiment result, it is concluded that this algorithm is superior to genetic algorithm and simulated annealing

Published in:

2006 IEEE International Conference on Service Operations and Logistics, and Informatics

Date of Conference:

21-23 June 2006