The Differential Evolution algorithm (DE) is a practical approach to global numerical optimization that is easy to understand, simple to implement, reliable, and fast. Packed with illustrations, computer code, new insights, and practical advice, this volume explores Differential Evolution (DE) in both principle and practice. It is a valuable resource for professionals needing a proven optimizer.

Depth of coverage. In-depth analysis of DE by its original creators that is not available elsewhere Expanded problem domains. Hands-on advice on how to apply DE to unconstrained, constrained, continuous and discrete numerical optimization problems New insights. The role of invariance principles in optimization and the similarities and differences between DE and other methods, like simulated annealing and evolution strategies New strategies. The latest extensions to the DE algorithm Applications. Real-world problems in signal processing, optical engineering, coding theory, robotics, etc., that have been solved by DE, many of which include comparisons to other optimization methods Includes supplementary material: sn.pub/extras

Zusammenfassung

From the reviews:

"This book is about an evolutionary method, called differential evolution (DE) ... . the authors claim that 'this book is designed to be easy to understand and simple to use'. Indeed, they have achieved their goal. The book is enjoyable to read, fully illustrated with figures and C-like pseudocodes ... . this book is foremost addressed to engineers ... . Moreover, those interested in evolutionary algorithms will certainly find this book to be both interesting and useful." (Panos M. Pardalos, Mathematical Reviews, Issue 2006 g)

Inhalt
Global optimization.- The Motivation for Differential Evolution.- Critical values for the control parameters of differential evolution algorithms.- The Differential Evolution Algorithm.- Fast Evolution Strategies.- Benchmarking Differential Evolution.- On the usage of differential evolution for function optimization.- Problem Domains.- Shape design and optimization by genetic algorithm.- Architectural Aspects and Computing Environments.- Computer Code.- Computer Code.- Applications.- Genetic Algorithms and Related Techniques for Optimizing Si-H Clusters: A Merit Analysis for Differential Evolution.- Non-Imaging Optical Design Using Differential Evolution.- Optimization of an Industrial Compressor Supply System.- Minimal Representation Multi-Sensor Fusion Using Differential Evolution.- Determination of the Earthquake Hypocenter: A Challenge for the Differential Evolution Algorithm.- Parallel Differential Evolution: Application to 3-D Medical Image Registration.- Design of Efficient Erasure Codes with Differential Evolution.- FIWIZ A Versatile Program for the Design of Digital Filters Using Differential Evolution.- Optimization of Radial Active Magnetic Bearings by Using Differential Evolution and the Finite Element Method.- Application of Differential Evolution to the Analysis of X-Ray Reflectivity Data.- Inverse Fractal Problem.- Active Compensation in RF-Driven Plasmas by Means of Differential Evolution.