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{ "item_title" : "Trends in Developing Metaheuristics, Algorithms, and Optimization Approaches", "item_author" : [" Peng-Yeng Yin "], "item_description" : "Developments in metaheuristics continue to advance computation beyond its traditional methods. With groundwork built on multidisciplinary research findings; metaheuristics, algorithms, and optimization approaches uses memory manipulations in order to take full advantage of strategic level problem solving. Trends in Developing Metaheuristics, Algorithms, and Optimization Approaches provides insight on the latest advances and analysis of technologies in metaheuristics computing. Offering widespread coverage on topics such as genetic algorithms, differential evolution, and ant colony optimization, this book aims to be a forum researchers, practitioners, and students who wish to learn and apply metaheuristic computing.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/1/46/662/145/1466621451_b.jpg", "price_data" : { "retail_price" : "195.00", "online_price" : "195.00", "our_price" : "195.00", "club_price" : "195.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Trends in Developing Metaheuristics, Algorithms, and Optimization Approaches|Peng-Yeng Yin

Trends in Developing Metaheuristics, Algorithms, and Optimization Approaches

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Overview

Developments in metaheuristics continue to advance computation beyond its traditional methods. With groundwork built on multidisciplinary research findings; metaheuristics, algorithms, and optimization approaches uses memory manipulations in order to take full advantage of strategic level problem solving. Trends in Developing Metaheuristics, Algorithms, and Optimization Approaches provides insight on the latest advances and analysis of technologies in metaheuristics computing. Offering widespread coverage on topics such as genetic algorithms, differential evolution, and ant colony optimization, this book aims to be a forum researchers, practitioners, and students who wish to learn and apply metaheuristic computing.

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Details

  • ISBN-13: 9781466621459
  • ISBN-10: 1466621451
  • Publisher: Igi Global Scientific Publishing
  • Publish Date: October 2012
  • Dimensions: 11.1 x 8.6 x 1 inches
  • Shipping Weight: 2.5 pounds
  • Page Count: 376

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