Skip to main content

Genetic Algorithms

Concepts and Designs

  • Textbook
  • © 1999

Overview

  • Gives the reader a complete overview of the latest discussions in the application of genetic algorithms to solve engineering problems
  • Real-world applications engage the reader with the complexities of the various genetic algorithms that are described
  • With the accompanying software, the reader has the opportunity to use an interactive genetic algorithms demonstration programme

Part of the book series: Advanced Textbooks in Control and Signal Processing (C&SP)

This is a preview of subscription content, log in via an institution to check access.

Access this book

eBook USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (10 chapters)

Keywords

About this book

Genetic Algorithms (GA) as a tool for a search and optimizing methodology has now reached a mature stage. It has found many useful applications in both the scientific and engineering arenas. The main reason for this success is undoubtedly due to the advances that have been made in solid-state microelectronics fabrication that have, in turn, led to the proliferation of widely available, low cost, and speedy computers. The GA works on the Darwinian principle of natural selection for which the noted English philosopher, Herbert Spencer coined the phrase "Survival of the fittest". As a numerical optimizer, the solutions obtained by the GA are not mathematically oriented. Instead, GA possesses an intrinsic flexibility and the freedom to choose desirable optima according to design specifications. Whether the criteria of concern be nonlinear, constrained, discrete, multimodal, or NP hard, the GA is entirely equal to the challenge. In fact, because of the uniqueness of the evolutionary process and the gene structure of a chromosome, the GA processing mechanism can take the form ofparallelism and multiobjective. These provide an extra dimension for solutions where other techniques may have failed completely. It is, therefore, the aim ofthis booktogather together relevant GA materialthat has already been used and demonstrated in various engineering disciplines.

Reviews

From the reviews:

This superb book is suitable for readers from a wide range of disciplines.

Assembly Automation 20 (2000) 86

 

This is a well-written engineering textbook. Genetic algorithms are properly explained and well motivated. The engineering examples illustrate the power of application of genetic algorithms.

Journal of the American Statistical Association March (2002) 366 (Reviewer: William F. Fulkerson)

 

The book is a good contribution to the genetic algorithm area from an applied point of view. It should be read by engineers, undergraduate or postgraduate students and researchers.

International Journal of Adaptive Control and Signal Processing 19 (2005) 59 – 62 (Reviewer: Doris Saez)

Authors and Affiliations

  • City University of Hong Kong, Kowloon, Hong Kong, China

    K. F. Man, K. S. Tang, S. Kwong

Bibliographic Information

Publish with us