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Nature-Inspired Optimization Algorithms with Java - Shashank Jain
Nature-Inspired Optimization Algorithms with Java - Shashank Jain

Nature-Inspired Optimization Algorithms with Java

Shashank Jain
pubblicato da Apress

Prezzo online:
41,17
45,68
-10 %
45,68

Gain insight into the world of nature-inspired optimization techniques and algorithms. This book will prepare you to apply different nature-inspired optimization techniques to solve problems using Java.

You'll start with an introduction to the hidden algorithms that nature uses and find the approximate solutions to optimization problems. You'll then see how living creatures such as fish and birds are able to perform computation to solve specific optimization tasks. This book also covers various nature-inspired algorithms by reviewing code examples for each one followed by crisp and clear explanations of the algorithm using Java code. You'll examine the use of each algorithm in specific industry scenarios such as fleet scheduling in supply chain management, and shop floor management in industrial and manufacturing applications.

Nature-Inspired Optimization Algorithms with Java is your pathway to understanding a variety of optimization problems that exist in various industries and domains and it will develop an ability to apply nature-inspired algorithms to find approximate solutions to them.

What You'll Learn

  • Study optimization and its problems
  • Examine nature-inspired algorithms such as Particle Swarm, Gray wolf, etc.
  • See how nature-inspired algorithms are being used to solve optimization problems
  • Use Java for solving the different nature-inspired algorithms with real-world examples

Who This Book Is For

Software developers/architects who are looking to hone their skills in area of problem solving related to optimization with Java.

Dettagli down

Generi Informatica e Web » Linguaggi e Applicazioni » Programmazione e sviluppo del software , Politica e Società » Comunicazione e Media » Internet, tecnologie e società

Editore Apress

Formato Ebook con Adobe DRM

Pubblicato 11/12/2021

Lingua Inglese

EAN-13 9781484274019

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