Advances in Evolutionary Algorithms PDF
Preview Advances in Evolutionary Algorithms
Advances in Evolutionary Algorithms Edited by Witold Kosinski Advances in Evolutionary Algorithms Edited by Witold Kosinski D3pZ4i & bhgvld, Dennixxx & rosea (for softarchive) DOI: 10.5772/73 Stole src from http://avaxho.me/blogs/exLib/ Published by AvE4EvA Copyright © 2008 All chapters are Open Access distributed under the Creative Commons Attribution 3.0 license, which allows users to download, copy and build upon published articles even for commercial purposes, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of our publications. After this work has been published, authors have the right to republish it, in whole or part, in any publication of which they are the author, and to make other personal use of the work. Any republication, referencing or personal use of the work must explicitly identify the original source. As for readers, this license allows users to download, copy and build upon published chapters even for commercial purposes, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of our publications. Notice Statements and opinions expressed in the chapters are these of the individual contributors and not necessarily those of the editors or publisher. No responsibility is accepted for the accuracy of information contained in the published chapters. The publisher assumes no responsibility for any damage or injury to persons or property arising out of the use of any materials, instructions, methods or ideas contained in the book. Publishing Process Manager Technical Editor AvE4EvA MuViMix Records Cover Designer ISBN-10 953-7619-11-7 ISBN-13 978-953-7619-11-4 C ontents Preface Part I: Foundations and New Methods 1 Limit Properties of Evolutionary Algorithms 2 Evolutionary Systems Identification: New Algorithmic Concepts and Applications 3 FPBIL: A Parameter-free E volutionary Algorithm Part II: Hybrid and Harmony Search 5 An Adaptive Evolutionary Algorithm Combining Evolution Strategy and Genetic Algorithm (Application of Fuzzy Power System Stabilizer) 6 A Simple Hybrid Particle Swarm Optimization 7 Pxecent Advances in Harmony Search A Hybrid Evolutionary Algorithm and its Application to Parameter Identification of Rolling Elements Bearings 9 Domain Decomposition Evolutionary Algorithm for Multi-Modal Function Optimization Part III: Dynamic Environment and Multi-Objective Optimization 10 Evolutionary A lgorithms with Dissortative Mating on Static and Dynamic Environments 11 Adapting Genetic Algorithms for Combinatorial Optimization Problems in Dy namic Environments 12 Agent-Based Co-Evolutionary Techniques for Solving Multi-Objective Optimization Problems 13 Evolutionary Multi-Objective PxObust Optimization 14 Improving InterpretabiIity of Fuzzy Models Using Multi-Objective Neuro-Evolution ary Algorithms 15 Multi-objective Uniform-divers ity Genetic Algorithm (MUG A) 16 EA-based Problem Solving Environment over the GRID VI Contents Part IV: Applications 17 Evolutionary Methods for Learning Bayesian Network Structures 18 Design of Phased Antenna Arrays using Evolutionary Optimization Techniques 19 Design of an Efficient Genetic Algorithm to Solve the Industrial C ar Sequencing Problem 20 Symbiotic Evolution Genetic Algorithms for Reinforcement Fuzzy Systems Design 21 Evolutionary Computation Applied to Urban Traffic Optimization 22 Evolutionary Algorithms in Decision Tree Induction Preface 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.
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