Advances in differential evolution

✍ Scribed by Rainer Storn (auth.), Uday K. Chakraborty (eds.)

• Publisher: Springer-Verlag Berlin Heidelberg
• Year: 2008
• Tongue: English
• Leaves: 340
• Series: Studies in Computational Intelligence 143
• Edition: 1
• Category: Library

✦ Synopsis

Differential evolution is arguably one of the hottest topics in today's computational intelligence research. This book seeks to present a comprehensive study of the state of the art in this technology and also directions for future research.

The fourteen chapters of this book have been written by leading experts in the area. The first seven chapters focus on algorithm design, while the last seven describe real-world applications. Chapter 1 introduces the basic differential evolution (DE) algorithm and presents a broad overview of the field. Chapter 2 presents a new, rotationally invariant DE algorithm. The role of self-adaptive control parameters in DE is investigated in Chapter 3. Chapters 4 and 5 address constrained optimization; the former develops suitable stopping conditions for the DE run, and the latter presents an improved DE algorithm for problems with very small feasible regions. A novel DE algorithm, based on the concept of "opposite" points, is the topic of Chapter 6. Chapter 7 provides a survey of multi-objective differential evolution algorithms. A review of the major application areas of differential evolution is presented in Chapter 8. Chapter 9 discusses the application of differential evolution in two important areas of applied electromagnetics. Chapters 10 and 11 focus on applications of hybrid DE algorithms to problems in power system optimization. Chapter 12 applies the DE algorithm to computer chess. The use of DE to solve a problem in bioprocess engineering is discussed in Chapter 13. Chapter 14 describes the application of hybrid differential evolution to a problem in control engineering.

✦ Table of Contents

Front Matter....Pages -
Differential Evolution Research – Trends and Open Questions....Pages 1-31
Eliminating Drift Bias from the Differential Evolution Algorithm....Pages 33-88
An Analysis of the Control Parameters’ Adaptation in DE....Pages 89-110
Stopping Criteria for Differential Evolution in Constrained Single-Objective Optimization....Pages 111-138
Constrained Optimization by ε Constrained Differential Evolution with Dynamic ε -Level Control....Pages 139-154
Opposition-Based Differential Evolution....Pages 155-171
Multi-objective Optimization Using Differential Evolution: A Survey of the State-of-the-Art....Pages 173-196
A Review of Major Application Areas of Differential Evolution....Pages 197-238
The Differential Evolution Algorithm as Applied to Array Antennas and Imaging....Pages 239-255
Applications of Differential Evolution in Power System Optimization....Pages 257-273
Self-adaptive Differential Evolution Using Chaotic Local Search for Solving Power Economic Dispatch with Nonsmooth Fuel Cost Function....Pages 275-286
An Adaptive Differential Evolution Algorithm with Opposition-Based Mechanisms, Applied to the Tuning of a Chess Program....Pages 287-298
Differential Evolution for the Offline and Online Optimization of Fed-Batch Fermentation Processes....Pages 299-317
Worst Case Analysis of Control Law for Re-entry Vehicles Using Hybrid Differential Evolution....Pages 319-333
Back Matter....Pages -

✦ Subjects

Appl.Mathematics/Computational Methods of Engineering; Artificial Intelligence (incl. Robotics)