Research Article
An Improved Genetic Algorithm on Task Scheduling
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@INPROCEEDINGS{10.1007/978-3-319-73317-3_57, author={Fangyuan Zheng and Jingmei Li}, title={An Improved Genetic Algorithm on Task Scheduling}, proceedings={Advanced Hybrid Information Processing. First International Conference, ADHIP 2017, Harbin, China, July 17--18, 2017, Proceedings}, proceedings_a={ADHIP}, year={2018}, month={2}, keywords={Task scheduling Heterogeneous multi-core processor Genetic algorithm Optimal solution}, doi={10.1007/978-3-319-73317-3_57} }- Fangyuan Zheng
Jingmei Li
Year: 2018
An Improved Genetic Algorithm on Task Scheduling
ADHIP
Springer
DOI: 10.1007/978-3-319-73317-3_57
Abstract
Efficient task scheduling algorithm is critical for achieving high performance in heterogeneous multi-core processors. Because the existing genetic algorithm converges to local optimal solution, so an improved genetic algorithm is proposed to solve the above problems in this thesis. Firstly, the initial population is generated randomly according to the task height value, and then adopting the selection strategy based on competition scale. Finally, the crossover and mutation probability is improved to avoid premature phenomenon. The experiment based on randomly generated graphs shows that the proposed algorithm can improve the efficiency of convergence.
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