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ASME Press Select Proceedings
International Conference on Electronics, Information and Communication Engineering (EICE 2012)
By
Garry Lee
Garry Lee
Information Engineering Research Institute
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ISBN:
9780791859971
No. of Pages:
1008
Publisher:
ASME Press
Publication date:
2012

As an effective global optimization method, genetic algorithm has been used in real practice very widely. When it is used in real practice, its slow convergence and poor stability have become the main problems. In order to overcome these problems, from the creation of the initial population, immune selection operation, improved genetic operators, et al, an improved fast immune genetic algorithm is proposed. Through the simulation experiments of some hard-optimization functions, the proposed algorithm shows its faster convergence and better stability than a lot of existing algorithms'.

Abstract
Keywords
Introduction
Improved Fast Immune Genetic Algorithm
Simulation Experiments
Conclusion
Acknowledgments
References
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