Multi Objective Optimization using Artificial Intelligence Techniques Book [PDF] Download

Download the fantastic book titled Multi Objective Optimization using Artificial Intelligence Techniques written by Seyedali Mirjalili, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Multi Objective Optimization using Artificial Intelligence Techniques", which was released on 24 July 2019. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Technology & Engineering genre.

Summary of Multi Objective Optimization using Artificial Intelligence Techniques by Seyedali Mirjalili PDF

This book focuses on the most well-regarded and recent nature-inspired algorithms capable of solving optimization problems with multiple objectives. Firstly, it provides preliminaries and essential definitions in multi-objective problems and different paradigms to solve them. It then presents an in-depth explanations of the theory, literature review, and applications of several widely-used algorithms, such as Multi-objective Particle Swarm Optimizer, Multi-Objective Genetic Algorithm and Multi-objective GreyWolf Optimizer Due to the simplicity of the techniques and flexibility, readers from any field of study can employ them for solving multi-objective optimization problem. The book provides the source codes for all the proposed algorithms on a dedicated webpage.


Detail About Multi Objective Optimization using Artificial Intelligence Techniques PDF

  • Author : Seyedali Mirjalili
  • Publisher : Springer
  • Genre : Technology & Engineering
  • Total Pages : 58 pages
  • ISBN : 3030248356
  • PDF File Size : 8,5 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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Multi-Objective Optimization Using Artificial Intelligence Techniques

Multi-Objective Optimization Using Artificial Intelligence Techniques
  • Publisher : Unknown Publisher
  • File Size : 55,6 Mb
  • Release Date : 17 June 2024
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This book focuses on the most well-regarded and recent nature-inspired algorithms capable of solving optimization problems with multiple objectives. Firstly, it provides preliminaries and essential definitions in multi-objective problems and

Multi-Objective Optimization using Artificial Intelligence Techniques

Multi-Objective Optimization using Artificial Intelligence Techniques
  • Publisher : Springer
  • File Size : 37,9 Mb
  • Release Date : 24 July 2019
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This book focuses on the most well-regarded and recent nature-inspired algorithms capable of solving optimization problems with multiple objectives. Firstly, it provides preliminaries and essential definitions in multi-objective problems and

Multi-Objective Machine Learning

Multi-Objective Machine Learning
  • Publisher : Springer Science & Business Media
  • File Size : 37,8 Mb
  • Release Date : 10 June 2007
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Recently, increasing interest has been shown in applying the concept of Pareto-optimality to machine learning, particularly inspired by the successful developments in evolutionary multi-objective optimization. It has been shown that

Bio-Inspired Systems: Computational and Ambient Intelligence

Bio-Inspired Systems: Computational and Ambient Intelligence
  • Publisher : Springer
  • File Size : 24,5 Mb
  • Release Date : 05 June 2009
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This volume presents the set of final accepted papers for the tenth edition of the IWANN conference “International Work-Conference on Artificial neural Networks” held in Salamanca (Spain) during June 10–12, 2009. IWANN

Multi-Objective Optimization using Evolutionary Algorithms

Multi-Objective Optimization using Evolutionary Algorithms
  • Publisher : John Wiley & Sons
  • File Size : 43,5 Mb
  • Release Date : 05 July 2001
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Optimierung mit mehreren Zielen, evolutionäre Algorithmen: Dieses Buch wendet sich vorrangig an Einsteiger, denn es werden kaum Vorkenntnisse vorausgesetzt. Geboten werden alle notwendigen Grundlagen, um die Theorie auf Probleme

Computational Intelligence in Optimization

Computational Intelligence in Optimization
  • Publisher : Springer Science & Business Media
  • File Size : 53,8 Mb
  • Release Date : 30 June 2010
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This collection of recent studies spans a range of computational intelligence applications, emphasizing their application to challenging real-world problems. Covers Intelligent agent-based algorithms, Hybrid intelligent systems, Machine learning and more.

Multi-Objective Optimization in Theory and Practice I: Classical Methods

Multi-Objective Optimization in Theory and Practice I: Classical Methods
  • Publisher : Bentham Science Publishers
  • File Size : 52,6 Mb
  • Release Date : 13 December 2017
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Multi-Objective Optimization in Theory and Practice is a traditional two-part approach to solving multi-objective optimization (MOO) problems namely the use of classical methods and evolutionary algorithms. This first book is

Applications Of Multi-objective Evolutionary Algorithms

Applications Of Multi-objective Evolutionary Algorithms
  • Publisher : World Scientific
  • File Size : 37,9 Mb
  • Release Date : 08 December 2004
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This book presents an extensive variety of multi-objective problems across diverse disciplines, along with statistical solutions using multi-objective evolutionary algorithms (MOEAs). The topics discussed serve to promote a wider understanding

Multiobjective Optimization

Multiobjective Optimization
  • Publisher : Springer
  • File Size : 20,7 Mb
  • Release Date : 18 October 2008
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Multiobjective optimization deals with solving problems having not only one, but multiple, often conflicting, criteria. Such problems can arise in practically every field of science, engineering and business, and the