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{ "item_title" : "An Introduction to Harmony Search Optimization Method", "item_author" : [" Xiaolei Wang", "Xiao-Zhi Gao", "Kai Zenger "], "item_description" : "This brief provides a detailed introduction, discussion and bibliographic review of the nature1-inspired optimization algorithm called Harmony Search. It uses a large number of simulation results to demonstrate the advantages of Harmony Search and its variants and also their drawbacks. The authors show how weaknesses can be amended by hybridization with other optimization methods. The Harmony Search Method with Applications will be of value to researchers in computational intelligence in demonstrating the state of the art of research on an algorithm of current interest. It also helps researchers and practitioners of electrical and computer engineering more generally in acquainting themselves with this method of vector-based optimization.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/3/31/908/355/3319083554_b.jpg", "price_data" : { "retail_price" : "54.99", "online_price" : "54.99", "our_price" : "54.99", "club_price" : "54.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
An Introduction to Harmony Search Optimization Method|Xiaolei Wang

An Introduction to Harmony Search Optimization Method

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Overview

This brief provides a detailed introduction, discussion and bibliographic review of the nature1-inspired optimization algorithm called Harmony Search. It uses a large number of simulation results to demonstrate the advantages of Harmony Search and its variants and also their drawbacks. The authors show how weaknesses can be amended by hybridization with other optimization methods. The Harmony Search Method with Applications will be of value to researchers in computational intelligence in demonstrating the state of the art of research on an algorithm of current interest. It also helps researchers and practitioners of electrical and computer engineering more generally in acquainting themselves with this method of vector-based optimization.

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Details

  • ISBN-13: 9783319083551
  • ISBN-10: 3319083554
  • Publisher: Springer
  • Publish Date: August 2014
  • Dimensions: 9.21 x 6.14 x 0.2 inches
  • Shipping Weight: 0.32 pounds
  • Page Count: 88

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