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This book is indexed in
Computer and Information Science » Numerical Analysis and Scientific Computing
Advances in Evolutionary Algorithms
Edited by Witold Kosinski, ISBN 978-953-7619-11-4, Hard cover, 284 pages, Publisher: InTech, Chapters published November 01, 2008 under CC BY-NC-SA 3.0 license
DOI: 10.5772/73 
With the recent trends towards massive data sets and significant computational power, combined with evolutionary algorithmic advances evolutionary computation is becoming much more relevant to practice. Aim of the book is to present recent improvements, innovative ideas and concepts in a part of a huge EA field.
- Chapter 1
Limit Properties of Evolutionary Algorithms - Chapter 2 Evolutionary Systems Identification: New Algorithmic Concepts and Applications
- Chapter 3 FPBIL: A Parameter-free Evolutionary Algorithm
- Chapter 4 A Memetic Algorithm Assisted by an Adaptive Topology RBF Network and Variable Local Models for Expensive Optimization Problems
- Chapter 5 An Adaptive Evolutionary Algorithm Combining Evolution Strategy and Genetic Algorithm (Application of Fuzzy Power System Stabilizer)
- Chapter 6 A Simple Hybrid Particle Swarm Optimization
- Chapter 7 Recent Advances in Harmony Search
- Chapter 8 A Hybrid Evolutionary Algorithm and its Application to Parameter Identification of Rolling Elements Bearings
- Chapter 9 Domain Decomposition Evolutionary Algorithm for Multi-Modal Function Optimization
- Chapter 10 Evolutionary Algorithms with Dissortative Mating on Static and Dynamic Environments
- Chapter 11 Adapting Genetic Algorithms for Combinatorial Optimization Problems in Dynamic Environments
- Chapter 12 Agent-Based Co-Evolutionary Techniques for Solving Multi-Objective Optimization Problems
- Chapter 13 Evolutionary Multi-Objective Robust Optimization
- Chapter 14 Improving Interpretability of Fuzzy Models Using Multi-Objective Neuro-Evolutionary Algorithms
- Chapter 15 Multi-objective Uniform-diversity Genetic Algorithm (MUGA)
- Chapter 16 EA-based Problem Solving Environment over the GRID
- Chapter 17 Evolutionary Methods for Learning Bayesian Network Structures
- Chapter 18 Design of Phased Antenna Arrays using Evolutionary Optimization Techniques
- Chapter 19 Design of an Efficient Genetic Algorithm to Solve the Industrial Car Sequencing Problem
- Chapter 20 Symbiotic Evolution Genetic Algorithms for Reinforcement Fuzzy Systems Design
- Chapter 21 Evolutionary Computation Applied to Urban Traffic Optimization
- Chapter 22 Evolutionary Algorithms in Decision Tree Induction