Music-Inspired Harmony Search Algorithm

Theory and Applications

  • Zong Woo Geem

Part of the Studies in Computational Intelligence book series (SCI, volume 191)

Table of contents

  1. Front Matter
  2. X. Z. Gao, X. Wang, S. J. Ovaska
    Pages 39-51
  3. Mehmet Polat Saka
    Pages 87-112
  4. Zong Woo Geem, Chung-Li Tseng, Justin C. Williams
    Pages 113-127
  5. Halim Ceylan, Huseyin Ceylan
    Pages 163-172
  6. Enrique Alexandre, Lucas Cuadra, Roberto Gil-Pita
    Pages 173-188
  7. Aditya Panchal
    Pages 189-203
  8. Back Matter

About this book


Calculus has been used in solving many scientific and engineering problems. For optimization problems, however, the differential calculus technique sometimes has a drawback when the objective function is step-wise, discontinuous, or multi-modal, or when decision variables are discrete rather than continuous. Thus, researchers have recently turned their interests into metaheuristic algorithms that have been inspired by natural phenomena such as evolution, animal behavior, or metallic annealing.

This book especially focuses on a music-inspired metaheuristic algorithm, harmony search. Interestingly, there exists an analogy between music and optimization: each musical instrument corresponds to each decision variable; musical note corresponds to variable value; and harmony corresponds to solution vector. Just like musicians in Jazz improvisation play notes randomly or based on experiences in order to find fantastic harmony, variables in the harmony search algorithm have random values or previously-memorized good values in order to find optimal solution.


Computational Intelligence Harmony Search Algorithm NP Soft Computing algorithms evolution metaheuristic modeling optimization

Editors and affiliations

  • Zong Woo Geem
    • 1
  1. 1.WestatRockvilleUSA

Bibliographic information

  • DOI
  • Copyright Information Springer Berlin Heidelberg 2009
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-3-642-00184-0
  • Online ISBN 978-3-642-00185-7
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • Buy this book on publisher's site
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