Hybrid Evolutionary Algorithms
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 ’Hybri...
| Συγγραφή απο Οργανισμό/Αρχή: | |
|---|---|
| Άλλοι συγγραφείς: | , , |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Berlin, Heidelberg :
Springer Berlin Heidelberg,
2007.
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| Σειρά: | Studies in Computational Intelligence,
75 |
| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- Hybrid Evolutionary Algorithms: Methodologies, Architectures, and Reviews
- Quantum-Inspired Evolutionary Algorithm for Numerical Optimization
- Enhanced Evolutionary Algorithms for Multidisciplinary Design Optimization: A Control Engineering Perspective
- Hybrid Evolutionary Algorithms and Clustering Search
- A Novel Hybrid Algorithm for Function Optimization: Particle Swarm Assisted Incremental Evolution Strategy
- An Efficient Nearest Neighbor Classifier
- Hybrid Genetic: Particle Swarm Optimization Algorithm
- A Hybrid Genetic Algorithm and Bacterial Foraging Approach for Global Optimization and Robust Tuning of PID Controller with Disturbance Rejection
- Memetic Algorithms Parametric Optimization for Microlithography
- Significance of Hybrid Evolutionary Computation for Ab Initio Protein Folding Prediction
- A Hybrid Evolutionary Heuristic for Job Scheduling on Computational Grids
- Clustering Gene-Expression Data: A Hybrid Approach that Iterates Between k-Means and Evolutionary Search
- Robust Parametric Image Registration
- Pareto Evolutionary Algorithm Hybridized with Local Search for Biobjective TSP.
