Scalable Optimization via Probabilistic Modeling
This book focuses like a laser beam on one of the hottest topics in evolutionary computation over the last decade or so: estimation of distribution algorithms (EDAs). EDAs are an important current technique that is leading to breakthroughs in genetic and evolutionary computation and in optimization...
Συγγραφή απο Οργανισμό/Αρχή: | |
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Άλλοι συγγραφείς: | , , |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
Berlin, Heidelberg :
Springer Berlin Heidelberg,
2006.
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Σειρά: | Studies in Computational Intelligence,
33 |
Θέματα: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- The Factorized Distribution Algorithm and the Minimum Relative Entropy Principle
- Linkage Learning via Probabilistic Modeling in the Extended Compact Genetic Algorithm (ECGA)
- Hierarchical Bayesian Optimization Algorithm
- Numerical Optimization with Real-Valued Estimation-of-Distribution Algorithms
- A Survey of Probabilistic Model Building Genetic Programming
- Efficiency Enhancement of Estimation of Distribution Algorithms
- Design of Parallel Estimation of Distribution Algorithms
- Incorporating a priori Knowledge in Probabilistic-Model Based Optimization
- Multiobjective Estimation of Distribution Algorithms
- Effective and Reliable Online Classification Combining XCS with EDA Mechanisms
- Military Antenna Design Using a Simple Genetic Algorithm and hBOA
- Feature Subset Selection with Hybrids of Filters and Evolutionary Algorithms
- BOA for Nurse Scheduling
- Searching for Ground States of Ising Spin Glasses with Hierarchical BOA and Cluster Exact Approximation.