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{ "item_title" : "Handbook of AI-based Metaheuristics", "item_author" : [" Anand J. Kulkarni", "Patrick Siarry "], "item_description" : "At the heart of the optimization domain are mathematical modeling of the problem and the solution methodologies. The problems are becoming larger and with growing complexity. Such problems are becoming cumbersome when handled by traditional optimization methods. This has motivated researchers to resort to artificial intelligence (AI)-based, nature-inspired solution methodologies or algorithms. The Handbook of AI-based Metaheuristics provides a wide-ranging reference to the theoretical and mathematical formulations of metaheuristics, including bio-inspired, swarm-based, socio-cultural, and physics-based methods or algorithms; their testing and validation, along with detailed illustrative solutions and applications; and newly devised metaheuristic algorithms. This will be a valuable reference for researchers in industry and academia, as well as for all Master's and PhD students working in the metaheuristics and applications domains.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/0/36/775/303/0367753030_b.jpg", "price_data" : { "retail_price" : "290.00", "online_price" : "290.00", "our_price" : "290.00", "club_price" : "290.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Handbook of AI-based Metaheuristics|Anand J. Kulkarni

Handbook of AI-based Metaheuristics

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Overview

At the heart of the optimization domain are mathematical modeling of the problem and the solution methodologies. The problems are becoming larger and with growing complexity. Such problems are becoming cumbersome when handled by traditional optimization methods. This has motivated researchers to resort to artificial intelligence (AI)-based, nature-inspired solution methodologies or algorithms.

The Handbook of AI-based Metaheuristics provides a wide-ranging reference to the theoretical and mathematical formulations of metaheuristics, including bio-inspired, swarm-based, socio-cultural, and physics-based methods or algorithms; their testing and validation, along with detailed illustrative solutions and applications; and newly devised metaheuristic algorithms.

This will be a valuable reference for researchers in industry and academia, as well as for all Master's and PhD students working in the metaheuristics and applications domains.

This item is Non-Returnable

Details

  • ISBN-13: 9780367753030
  • ISBN-10: 0367753030
  • Publisher: CRC Press
  • Publish Date: September 2021
  • Dimensions: 9.61 x 6.69 x 0.94 inches
  • Shipping Weight: 1.91 pounds
  • Page Count: 398

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