Modern Heuristic Optimization Techniques

This book provides readers with basic knowledge of evolutionary computation and other heuristic optimization techniques, and explains how they are combined with knowledge elements in computational intelligence systems. Applications to power problems are stressed, and example applications are presented. The first book to offer a comprehensive overview of the wide range of modern heuristic optimization techniques in a unified way for general readers, it provides a wealth of information on practical applications in power systems for practicing engineers. Coverage includes the fundamentals of evolutionary computation, genetic algorithms, evolutionary programming and strategies, simulated annealing, tabu search, and hybrid system of evolutionary computation, plus an overview of power system applications. The text also discusses specific applications of the heuristic approaches to power system problems, such as security assessment, operational planning, generation, transmission and distribution planning, state estimation, and power plant and power system control.

Kwang Y. Lee, PhD, is a Professor and Chair of Electrical and Computer Engineering at Baylor University (Texas). He is a Fellow of the IEEE. He was an associate editor of IEEE Transactions on Neural Networks and is an Editor of IEEE Transactions on Energy Conversion. He was also a member of the board of directors of the International Conference on Intelligent System Applications to Power Systems (ISAP).

Mohamed A. El-Sharkawi, PhD, is a Professor of Electrical Engineering at the University of Washington. He is a Fellow of the IEEE, founder of the International Forum on the Application of Neural Networks to Power Systems (ANNPS), and cofounder of the International Conference on Intelligent System Applications to Power Systems (ISAP).

Preface
Contributors
Theory of Modern Heuristic Optimization
Introduction to Evolutionary Computation
Fundamentals of Genetic Algorithms
Fundamentals of Evolution Strategies and Evolutionary Programming
Fundamentals of Particle Swarm Optimization Techniques
Fundamentals of Ant Colony Search Algorithms
Fundamentals of Tabu Search
Fundamentals of Simulated Annealing
Fuzzy Systems
Differential Evolution, an Alternative Approach to Evolutionary Algorithm
Pareto Multiobjective Optimization
Trust-Tech Paradigm for Computing High-Quality Optimal Solutions: Method and Theory
Selected Applications of Modern Heuristic Optimization in Power Systems
Overview of Applications in Power Systems
Application of Evolutionary Technique to Power System Vulnerability Assessment
Applications to System Planning
Applications to Power System Scheduling
Power System Controls
Genetic Algorithms for Solving Optimal Power Flow Problems
An Interactive Compromise Programming-Based Multiobjective Approach to FACTS Control
Hybrid Systems
Index
Table of Contents provided by Publisher. All Rights Reserved.

What is included with this book?

The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any access cards, study guides, lab manuals, CDs, etc.

The Used, Rental and eBook copies of this book are not guaranteed to include any supplemental materials. Typically, only the book itself is included. This is true even if the title states it includes any access cards, study guides, lab manuals, CDs, etc.

FREE SHIPPING

Rent More, Save More! Use code: BBRENTAL

5% off 1 book, 7% off 2 books, 10% off 3+ books

Modern Heuristic Optimization Techniques Theory and Applications to Power Systems

Summary

Author Biography

Table of Contents

Supplemental Materials