Abstract
Organisms are one of the most wonderful systems in the world. Like the method of the last chapter, we introduce here another powerful problem solving technique inspired from biology. Genetic algorithm, just like simulated annealing, is suitable to both combinatorial and numerical optimizations. They find wide applications in different research fields, such as management, engineering, industrial design, and so forth.
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References
The genetic algorithm was first realized in, J. Holland, “Adaptation in Natural and Artificial Systems”, University of Michigan Press, Ann Arbor (1975)
The following introduces various applications of genetic algorithm, D.E. Goldberg, “Genetic Algorithms in Search, Optimization & Machine Learning”, Addison-Wesley, Reading, Massachusetts (1989)
Genetic programming was presented by, J. Koza, “Genetic Programming”, MIT Press, Cambridge, MA (1992)
A review of evolving artificial neural networks is, X. Yao, “Evolving Artificial Neural Networks”, Proceedings of the IEEE, 87(9) (1999) 1423–1447
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© 2003 Springer Science+Business Media New York
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Wang, SC. (2003). Genetic Algorithm. In: Interdisciplinary Computing in Java Programming. The Springer International Series in Engineering and Computer Science, vol 743. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-0377-4_6
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DOI: https://doi.org/10.1007/978-1-4615-0377-4_6
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-5046-0
Online ISBN: 978-1-4615-0377-4
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