Cider - Shop now
Buy new:
-11% $127.23
FREE delivery Thursday, May 15 to Nashville 37217
Ships from: Amazon.com
Sold by: Amazon.com
$127.23 with 11 percent savings
List Price: $142.95
FREE Returns
FREE delivery Thursday, May 15 to Nashville 37217
Or fastest delivery Wednesday, May 14. Order within 4 hrs 22 mins
Only 2 left in stock (more on the way).
$$127.23 () Includes selected options. Includes initial monthly payment and selected options. Details
Price
Subtotal
$$127.23
Subtotal
Initial payment breakdown
Shipping cost, delivery date, and order total (including tax) shown at checkout.
Ships from
Amazon.com
Amazon.com
Ships from
Amazon.com
Sold by
Amazon.com
Amazon.com
Sold by
Amazon.com
Returns
30-day refund/replacement
30-day refund/replacement
This item can be returned in its original condition for a full refund or replacement within 30 days of receipt.
Read full return policy
Payment
Secure transaction
Your transaction is secure
We work hard to protect your security and privacy. Our payment security system encrypts your information during transmission. We don’t share your credit card details with third-party sellers, and we don’t sell your information to others. Learn more
$99.87
FREE Returns
Book in good condition. Ships direct from Amazon! An estate item from the library of an industry professional. Pages are crisp and clean; no markings noticed. Light wear on cover, corners and edges. Individually inspected by John & Kristin. Thank you for supporting our small business. Book in good condition. Ships direct from Amazon! An estate item from the library of an industry professional. Pages are crisp and clean; no markings noticed. Light wear on cover, corners and edges. Individually inspected by John & Kristin. Thank you for supporting our small business. See less
FREE delivery Thursday, May 15 to Nashville 37217
Or Prime members get FREE delivery Tuesday, May 13. Order within 4 hrs 22 mins.
Only 1 left in stock - order soon.
$$127.23 () Includes selected options. Includes initial monthly payment and selected options. Details
Price
Subtotal
$$127.23
Subtotal
Initial payment breakdown
Shipping cost, delivery date, and order total (including tax) shown at checkout.
Access codes and supplements are not guaranteed with used items.
Kindle app logo image

Download the free Kindle app and start reading Kindle books instantly on your smartphone, tablet, or computer - no Kindle device required.

Read instantly on your browser with Kindle for Web.

Using your mobile phone camera - scan the code below and download the Kindle app.

QR code to download the Kindle App

Follow the author

Dan Simon
Follow
Something went wrong. Please try your request again later.

Evolutionary Optimization Algorithms 1st Edition

by Dan Simon (Author)
4.8 out of 5 stars 15 ratings
{"desktop_buybox_group_1":[{"displayPrice":"$127.23","priceAmount":127.23,"currencySymbol":"$","integerValue":"127","decimalSeparator":".","fractionalValue":"23","symbolPosition":"left","hasSpace":false,"showFractionalPartIfEmpty":true,"offerListingId":"2RE5p1PWgdamJ0WRAtWED8DoWORfNPZUdt4SCx3BEeZAjOI8%2FQqt4TwhWnqaO%2FeqZorRWo%2FOongRWMq7Bxs4it%2FNBLhRTLHrWpcopCGLJlLIXPFcSe255r3xuiC6a7O1S4pa2lIySRUBCbaiRuJqRA%3D%3D","locale":"en-US","buyingOptionType":"NEW","aapiBuyingOptionIndex":0}, {"displayPrice":"$99.87","priceAmount":99.87,"currencySymbol":"$","integerValue":"99","decimalSeparator":".","fractionalValue":"87","symbolPosition":"left","hasSpace":false,"showFractionalPartIfEmpty":true,"offerListingId":"2RE5p1PWgdamJ0WRAtWED8DoWORfNPZU2VTDxDDGlV5yu6rWJELEYQe4Yqivbpmn0pSJKGeaK3AIyFzvOUsiOgoBw38r%2BidhxK5nQr7zzv1fpt%2F9JEpLM4wDcx%2BVP2%2Beg0XoAlJWuOzIZHvaWa2z4g7d8QyoDrmQC1B8XK2GBdYJx9ze0dHdv5OIsESQl1XR","locale":"en-US","buyingOptionType":"USED","aapiBuyingOptionIndex":1}]}

Purchase options and add-ons

A clear and lucid bottom-up approach to the basic principles of evolutionary algorithms

Evolutionary algorithms (EAs) are a type of artificial intelligence. EAs are motivated by optimization processes that we observe in nature, such as natural selection, species migration, bird swarms, human culture, and ant colonies.

This book discusses the theory, history, mathematics, and programming of evolutionary optimization algorithms. Featured algorithms include genetic algorithms, genetic programming, ant colony optimization, particle swarm optimization, differential evolution, biogeography-based optimization, and many others.

Evolutionary Optimization Algorithms:

  • Provides a straightforward, bottom-up approach that assists the reader in obtaining a clear—but theoretically rigorous—understanding of evolutionary algorithms, with an emphasis on implementation
  • Gives a careful treatment of recently developed EAs—including opposition-based learning, artificial fish swarms, bacterial foraging, and many others— and discusses their similarities and differences from more well-established EAs
  • Includes chapter-end problems plus a solutions manual available online for instructors
  • Offers simple examples that provide the reader with an intuitive understanding of the theory
  • Features source code for the examples available on the author's website
  • Provides advanced mathematical techniques for analyzing EAs, including Markov modeling and dynamic system modeling

Evolutionary Optimization Algorithms: Biologically Inspired and Population-Based Approaches to Computer Intelligence is an ideal text for advanced undergraduate students, graduate students, and professionals involved in engineering and computer science.

Read more
Previous slide of product details
  1. ISBN-10
    0470937416
  2. ISBN-13
    978-0470937419
  3. Edition
    1st
  4. Publisher
    Wiley
  5. Publication date
    April 29, 2013
  6. Language
    English
  7. Dimensions
    6.3 x 1.9 x 9.4 inches
  8. Print length
    784 pages
Next slide of product details

Frequently bought together

Evolutionary Optimization Algorithms
This item: Evolutionary Optimization Algorithms
$127.23
Get it as soon as Thursday, May 15
Only 2 left in stock (more on the way).
Ships from and sold by Amazon.com.
+
Evolutionary Computation: A Unified Approach
$40.00
Get it as soon as Thursday, May 15
In Stock
Ships from and sold by Amazon.com.
Total price: $00
To see our price, add these items to your cart.
Details
Added to Cart
One of these items ships sooner than the other.
Show details Hide details
Choose items to buy together.

Editorial Reviews

From the Inside Flap

A clear and lucid bottom-up approach to the basic principles of evolutionary algorithms

Evolutionary algorithms (EAs) are a type of artificial intelligence. EAs are motivated by optimization processes that we observe in nature, such as natural selection, species migration, bird swarms, human culture, and ant colonies.

This book discusses the theory, history, mathematics, and programming of evolutionary optimization algorithms. Featured algorithms include genetic algorithms, genetic programming, ant colony optimization, particle swarm optimization, differential evolution, biogeography-based optimization, and many others.

Evolutionary Optimization Algorithms:

  • Provides a straightforward, bottom-up approach that assists the reader in obtaining a clear—but theoretically rigorous—understanding of evolutionary algorithms, with an emphasis on implementation
  • Gives a careful treatment of recently developed EAs—including opposition-based learning, artificial fish swarms, bacterial foraging, and many others— and discusses their similarities and differences from more well-established EAs
  • Includes chapter-end problems plus a solutions manual available online for instructors
  • Offers simple examples that provide the reader with an intuitive understanding of the theory
  • Features source code for the examples available on the author's website
  • Provides advanced mathematical techniques for analyzing EAs, including Markov modeling and dynamic system modeling

Evolutionary Optimization Algorithms: Biologically Inspired and Population-Based Approaches to Computer Intelligence is an ideal text for advanced undergraduate students, graduate students, and professionals involved in engineering and computer science.

From the Back Cover

A clear and lucid bottom-up approach to the basic principles of evolutionary algorithms

Evolutionary algorithms (EAs) are a type of artificial intelligence. EAs are motivated by optimization processes that we observe in nature, such as natural selection, species migration, bird swarms, human culture, and ant colonies.

This book discusses the theory, history, mathematics, and programming of evolutionary optimization algorithms. Featured algorithms include genetic algorithms, genetic programming, ant colony optimization, particle swarm optimization, differential evolution, biogeography-based optimization, and many others.

Evolutionary Optimization Algorithms:

  • Provides a straightforward, bottom-up approach that assists the reader in obtaining a clear but theoretically rigorous understanding of evolutionary algorithms, with an emphasis on implementation
  • Gives a careful treatment of recently developed EAs including opposition-based learning, artificial fish swarms, bacterial foraging, and many others and discusses their similarities and differences from more well-established EAs
  • Includes chapter-end problems plus a solutions manual available online for instructors
  • Offers simple examples that provide the reader with an intuitive understanding of the theory
  • Features source code for the examples available on the author's website
  • Provides advanced mathematical techniques for analyzing EAs, including Markov modeling and dynamic system modeling

Evolutionary Optimization Algorithms: Biologically Inspired and Population-Based Approaches to Computer Intelligence is an ideal text for advanced undergraduate students, graduate students, and professionals involved in engineering and computer science.

Product details

  • Publisher ‏ : ‎ Wiley; 1st edition (April 29, 2013)
  • Language ‏ : ‎ English
  • Hardcover ‏ : ‎ 784 pages
  • ISBN-10 ‏ : ‎ 0470937416
  • ISBN-13 ‏ : ‎ 978-0470937419
  • Item Weight ‏ : ‎ 2.6 pounds
  • Dimensions ‏ : ‎ 6.3 x 1.9 x 9.4 inches
  • Customer Reviews:
    4.8 out of 5 stars 15 ratings

About the author

Follow authors to get new release updates, plus improved recommendations.
Dan Simon

Dan Simon

Brief content visible, double tap to read full content.
Full content visible, double tap to read brief content.

I was born at a very young age in California, but I don't remember too much about California because my family moved to Phoenix when I was 2 or 3 years old. I lived in Phoenix until I was 22 years old, receiving my BSEE from Arizona State University in 1982. I then got a job with Boeing and lived in Seattle until 1988, earning my MSEE along the way during part-time studies at the University of Washington. In 1988 I resigned from Boeing and moved to Syracuse to study full-time, earning my PhD in 1991. I then worked for a variety of engineering companies, ranging from multi-billion dollar corporations to my own one-man consulting business. I begin working at Cleveland State University in 1999 as a full-time professor, and I've been there ever since. You can read more about my research and other interests at my web page: http://academic.csuohio.edu/simond. That web page also has links to the web pages for my books, where you can download lots of sample code (Matlab), and where you can see how to get the solution manuals if you are a course instructor.

Customer reviews

4.8 out of 5 stars
15 global ratings

Review this product

Share your thoughts with other customers
Write a customer review

Top reviews from the United States

  • agt27
    5.0 out of 5 stars Excellent comprehensive text!
    Reviewed in the United States on February 28, 2025
    Verified Purchase
    The organization of the book is well constructed. There is a nice balance between text to explain the concepts, algorithms to implement, and figures to illustrate. Highly recommended!
    One person found this helpful
    Helpful
     Report
  • James Tolton
    5.0 out of 5 stars Not just a great EA book, not just a great programming book, but overall a great book
    Reviewed in the United States on February 1, 2024
    Verified Purchase
    I happily sit this book on bookshelf right next to "Artificial Intelligence: A Modern Approach", if that means anything to you. I loved this book, and I can't say enough great things about it.

    The first thing that comes to mind is *respect for the reader*. Every word, formula, and algorithm is written with careful consideration to add value to the reader. Nothing in this book feels like filler, a waste of time, out of place, or incomplete.

    There are a few points for which I am extremely grateful:

    1. Accessible and consistent mathematical notation. I should note that I am an industry practitioner, not an academic. That's why I was extremely appreciative that the author uses a limited and consistent number of mathematical tools which are clearly explained. Where necessary, the derivation and proofs are provided, allowing a curious or demanding reader to extract as much or little detail as required to understand the concept to their satisfaction.

    I can only imagine the effort that went in to unifying the notation across all the papers and subdisciplines into a single consistent language!

    2. Readability -- you can pick this book up and read it cover to cover. If you have an interest in the area, the book is extremely engaging and quite the page turner!

    3. The right amount of detail (and abstraction) -- most of the algorithms provided by the author could fit on an index card. The author does a great job of mixing together technical prose, mathematical notation, and descriptive flow control and conditional terminology such that you can easily imagine implementing the algorithm in your preferred language.

    It's really hard to stress this point enough. The algorithms are written in such a way that you can understand the entire thing in a single reading. It's not like a scientific paper or certain textbooks I've read where you need to spend hours or days on a single page or formula to untangle it.

    For comparison, I am the sort that when I'm reading a journal article or paper, my eyes typically gloss over the formulas, especially if it's not a field that I'm particularly familiar with. If I'm interested enough in the paper, I'll go back and wrestle with the formulas later.

    That is not the case here. I found myself just as eager for the next formula or algorithm as I was for the next prosaic explanation. Despite the thickness of the book, the pages practically turned themselves!
    3 people found this helpful
    Helpful
     Report
  • NeilS
    5.0 out of 5 stars A good overview of EA
    Reviewed in the United States on April 29, 2014
    Verified Purchase
    This hits pretty much everything you need to know to get started with EAs. It is really nice to have a self contained volume like this instead of my giant stack of peer reviewed papers. Granted, the papers do get into more detail with the specific topics the address, but this book has been useful in helping to explain EAs to my coworkers here at the R&D firm I work at. The code supplements are also pretty nice references to get started (MATLAB). Check out [...]. The only gripe I have with the book is some use of LISP in the text (not a fan), but that isn't an integral part of the book and you don't need to use LISP to get a good understanding on how EAs work when using this book.
    6 people found this helpful
    Helpful
     Report
  • Andrew
    5.0 out of 5 stars Seriously good book in Computer Science and Evolutionary Algorithms
    Reviewed in the United States on June 10, 2018
    Verified Purchase
    After taking 6 months to read this book, I can only say what a truly impressive exploration of the subject. I rate this as a 5-stars for many reasons. It isn’t just a good book on Evolutionary Algorithms but also an important book for Computer Science in general. I think this is one of the great books that no one noticed. Have fun reading this book!
    One person found this helpful
    Helpful
     Report
  • A customer
    5.0 out of 5 stars Great Book
    Reviewed in the United States on March 19, 2021
    Verified Purchase
    Clear and comprehensive.
    Helpful
     Report
  • David K. vun Kannon
    5.0 out of 5 stars Great coverage of topics
    Reviewed in the United States on June 5, 2014
    Verified Purchase
    Dan Simon does a really good job of surveying the field of evolutionary optimization algorithms. The text is up to date and well balanced across the many variants of evolutionary computation.
    2 people found this helpful
    Helpful
     Report
  • GCHEN
    5.0 out of 5 stars Five Stars
    Reviewed in the United States on March 6, 2015
    Verified Purchase
    it is very good.fast and excellent
    One person found this helpful
    Helpful
     Report
  • Komkrit
    5.0 out of 5 stars Five Stars
    Reviewed in the United States on May 6, 2015
    Verified Purchase
    good book
    Helpful
     Report