© 2005

Differential Evolution

A Practical Approach to Global Optimization


  • 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


Part of the Natural Computing Series book series (NCS)

Table of contents

  1. Front Matter
    Pages I-XIX
  2. Global optimization

  3. Critical values for the control parameters of differential evolution algorithms

  4. Fast Evolution Strategies

  5. On the usage of differential evolution for function optimization

    1. Pages 189-265
  6. Shape design and optimization by genetic algorithm

  7. Computer Code

    1. Pages 287-309
  8. Applications

    1. Front Matter
      Pages 311-312
    2. David Corcoran, Steven Doyle
      Pages 327-337
    3. Evan P. Hancox, Robert W. Derksen
      Pages 339-351
    4. Rajive Joshi, Arthur C. Sanderson
      Pages 353-377
    5. Michel Salomon, Guy-René Perrin, Fabrice Heitz, J.-P. Armspach
      Pages 353-411
    6. Amin Shokrollahi, Rainer Storn
      Pages 413-427
    7. Matthew Wormington, Kevin M. Matney, D. Keith Bowen
      Pages 463-478
    8. Ivan Zelinka
      Pages 479-498

About this book


Problems demanding globally optimal solutions are ubiquitous, yet many are intractable when they involve constrained functions having many local optima and interacting, mixed-type variables.

The differential evolution (DE) algorithm is a practical approach to global numerical optimization which is easy to understand, simple to implement, reliable, and fast. Packed with illustrations, computer code, new insights, and practical advice, this volume explores DE in both principle and practice. It is a valuable resource for professionals needing a proven optimizer and for students wanting an evolutionary perspective on global numerical optimization.


Design Differential evolution Evolutionary computation Genetic Algorithms Global optimization Numerical optimization Variable algorithms computer optimization

Authors and affiliations

  1. 1.VacavilleUSA
  2. 2.Rohde & Schwarz GmbH & Co. KGMünchenGermany
  3. 3.Department of Information TechnologyLappeenranta University of TechnologyLappeenrantaFinland

Bibliographic information

Industry Sectors
Finance, Business & Banking


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)