menu
{ "item_title" : "Nature-Inspired Algorithms and Applied Optimization", "item_author" : [" Xin-She Yang "], "item_description" : "Reviews the state-of-the-art developments in nature-inspired algorithms and optimization Presents a number of theories (no-free-lunch theorems and convergence analysis) and insights into nature-inspired algorithms Introduces algorithms with an emphasis on applied optimization in real-world applications", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/3/31/967/668/3319676687_b.jpg", "price_data" : { "retail_price" : "199.99", "online_price" : "199.99", "our_price" : "199.99", "club_price" : "199.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Nature-Inspired Algorithms and Applied Optimization|Xin-She Yang

Nature-Inspired Algorithms and Applied Optimization

local_shippingShip to Me
In Stock.
FREE Shipping for Club Members help

Overview

Reviews the state-of-the-art developments in nature-inspired algorithms and optimization

Presents a number of theories (no-free-lunch theorems and convergence analysis) and insights into nature-inspired algorithms

Introduces algorithms with an emphasis on applied optimization in real-world applications

This item is Non-Returnable

Details

  • ISBN-13: 9783319676685
  • ISBN-10: 3319676687
  • Publisher: Springer
  • Publish Date: October 2017
  • Dimensions: 9.21 x 6.14 x 0.81 inches
  • Shipping Weight: 1.45 pounds
  • Page Count: 330

Related Categories

You May Also Like...

    1

BAM Customer Reviews