Hybridization of evolutionary algorithms is getting popular due to their capabilities in handling several real world problems involving complexity, noisy environment, imprecision, uncertainty and vagueness. This edited volume is targeted to present the latest state-of-the-art methodologies in βHybri
[Studies in Computational Intelligence] Intelligent and Evolutionary Systems Volume 187 || Evolutionary Network Design by Multiobjective Hybrid Genetic Algorithm
β Scribed by Gen, Mitsuo; Green, David; Katai, Osamu; McKay, Bob; Namatame, Akira; Sarker, Ruhul A.; Zhang, Byoung-Tak
- Book ID
- 120427189
- Publisher
- Springer Berlin Heidelberg
- Year
- 2009
- Weight
- 369 KB
- Category
- Article
- ISBN
- 3540959785
No coin nor oath required. For personal study only.
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Hybridization of evolutionary algorithms is getting popular due to their capabilities in handling several real world problems involving complexity, noisy environment, imprecision, uncertainty and vagueness. This edited volume is targeted to present the latest state-of-the-art methodologies in βHybri
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