Abstract
This paper deals with an important class of optimization problems, the multiobjective problems. A new genetic algorithm, called the dual genetic algorithm, is presented. Through two theoretical problems, we show that this approach appears to be efficient for multiobjective optimization.
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© 1998 Springer-Verlag Wien
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Clergue, M., Collard, P. (1998). Dual Genetic Algorithms and Pareto Optimization. In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6492-1_41
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DOI: https://doi.org/10.1007/978-3-7091-6492-1_41
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-83087-1
Online ISBN: 978-3-7091-6492-1
eBook Packages: Springer Book Archive