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{ "item_title" : "Evolutionary Algorithms for Solving Multi-Objective Problems", "item_author" : [" Carlos Coello Coello", "Gary B. Lamont", "David A. Van Veldhuizen "], "item_description" : "This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom, with links to a complete set of teaching tutorials, exercises and solutions. The book contains exhaustive appendices, index and bibliography. The various features of multi-objective evolutionary algorithms are presented here in an innovative and student-friendly fashion, incorporating state-of-the-art research. The book disseminates the application of evolutionary algorithm techniques to a variety of practical problems, including test suites with associated performance based on a variety of appropriate metrics, as well as serial and parallel algorithm implementations.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/0/38/733/254/0387332545_b.jpg", "price_data" : { "retail_price" : "149.00", "online_price" : "149.00", "our_price" : "149.00", "club_price" : "149.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Evolutionary Algorithms for Solving Multi-Objective Problems|Carlos Coello Coello

Evolutionary Algorithms for Solving Multi-Objective Problems

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Overview

This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom, with links to a complete set of teaching tutorials, exercises and solutions. The book contains exhaustive appendices, index and bibliography. The various features of multi-objective evolutionary algorithms are presented here in an innovative and student-friendly fashion, incorporating state-of-the-art research. The book disseminates the application of evolutionary algorithm techniques to a variety of practical problems, including test suites with associated performance based on a variety of appropriate metrics, as well as serial and parallel algorithm implementations.

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Details

  • ISBN-13: 9780387332543
  • ISBN-10: 0387332545
  • Publisher: Springer
  • Publish Date: September 2007
  • Dimensions: 9.25 x 6.48 x 1.67 inches
  • Shipping Weight: 2.87 pounds
  • Page Count: 800

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