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Handbook of Nature-Inspired Optimization Algorithms: The State of the Art

2022-08-31 Technology & Engineering
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Release : 2022-08-31
Genre : Technology & Engineering
Kind : eBook
Book Rating : 129/5 ( reviews)

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Book Synopsis Handbook of Nature-Inspired Optimization Algorithms: The State of the Art by : Ali Mohamed

Download or read book Handbook of Nature-Inspired Optimization Algorithms: The State of the Art written by Ali Mohamed. This book was released on 2022-08-31. Available in PDF, EPUB and Kindle. Book excerpt: The introduction of nature-inspired optimization algorithms (NIOAs), over the past three decades, helped solve nonlinear, high-dimensional, and complex computational optimization problems. NIOAs have been originally developed to overcome the challenges of global optimization problems such as nonlinearity, non-convexity, non-continuity, non-differentiability, and/or multimodality which traditional numerical optimization techniques had difficulties solving. The main objective for this book is to make available a self-contained collection of modern research addressing the general bound-constrained optimization problems in many real-world applications using nature-inspired optimization algorithms. This book is suitable for a graduate class on optimization, but will also be useful for interested senior students working on their research projects.

Solving Constrained Single Objective Real-parameter Optimization Problems

2022
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Release : 2022
Genre :
Kind : eBook
Book Rating : 179/5 ( reviews)

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Book Synopsis Solving Constrained Single Objective Real-parameter Optimization Problems by : Ali Mohamed

Download or read book Solving Constrained Single Objective Real-parameter Optimization Problems written by Ali Mohamed. This book was released on 2022. Available in PDF, EPUB and Kindle. Book excerpt:

Handbook of Nature-Inspired Optimization Algorithms: The State of the Art

2022-09-03 Technology & Engineering
Download Handbook of Nature-Inspired Optimization Algorithms: The State of the Art PDF Online Free

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Release : 2022-09-03
Genre : Technology & Engineering
Kind : eBook
Book Rating : 161/5 ( reviews)

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Book Synopsis Handbook of Nature-Inspired Optimization Algorithms: The State of the Art by : Ali Wagdy Mohamed

Download or read book Handbook of Nature-Inspired Optimization Algorithms: The State of the Art written by Ali Wagdy Mohamed. This book was released on 2022-09-03. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent contributions and significant development, advanced issues, and challenges. In real-world problems and applications, most of the optimization problems involve different types of constraints. These problems are called constrained optimization problems (COPs). The optimization of the constrained optimization problems is considered a challenging task since the optimum solution(s) must be feasible. In their original design, evolutionary algorithms (EAs) are able to solve unconstrained optimization problems effectively. As a result, in the past decade, many researchers have developed a variety of constraint handling techniques, incorporated into (EAs) designs, to counter this deficiency. The main objective for this book is to make available a self-contained collection of modern research addressing the general constrained optimization problems in many real-world applications using nature-inspired optimization algorithms. This book is suitable for a graduate class on optimization, but will also be useful for interested senior students working on their research projects.

Nature-Inspired Optimization Algorithms

2021-02-08 Computers
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Release : 2021-02-08
Genre : Computers
Kind : eBook
Book Rating : 15X/5 ( reviews)

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Book Synopsis Nature-Inspired Optimization Algorithms by : Aditya Khamparia

Download or read book Nature-Inspired Optimization Algorithms written by Aditya Khamparia. This book was released on 2021-02-08. Available in PDF, EPUB and Kindle. Book excerpt: This book will focus on the involvement of data mining and intelligent computing methods for recent advances in Biomedical applications and algorithms of nature-inspired computing for Biomedical systems. The proposed meta heuristic or nature-inspired techniques should be an enhanced, hybrid, adaptive or improved version of basic algorithms in terms of performance and convergence metrics. In this exciting and emerging interdisciplinary area a wide range of theory and methodologies are being investigated and developed to tackle complex and challenging problems. Today, analysis and processing of data is one of big focuses among researchers community and information society. Due to evolution and knowledge discovery of natural computing, related meta heuristic or bio-inspired algorithms have gained increasing popularity in the recent decade because of their significant potential to tackle computationally intractable optimization dilemma in medical, engineering, military, space and industry fields. The main reason behind the success rate of nature inspired algorithms is their capability to solve problems. The nature inspired optimization techniques provide adaptive computational tools for the complex optimization problems and diversified engineering applications. Tentative Table of Contents/Topic Coverage: - Neural Computation - Evolutionary Computing Methods - Neuroscience driven AI Inspired Algorithms - Biological System based algorithms - Hybrid and Intelligent Computing Algorithms - Application of Natural Computing - Review and State of art analysis of Optimization algorithms - Molecular and Quantum computing applications - Swarm Intelligence - Population based algorithm and other optimizations

Nature-Inspired Optimization Algorithms

2020-09-09 Science
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Release : 2020-09-09
Genre : Science
Kind : eBook
Book Rating : 890/5 ( reviews)

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Book Synopsis Nature-Inspired Optimization Algorithms by : Xin-She Yang

Download or read book Nature-Inspired Optimization Algorithms written by Xin-She Yang. This book was released on 2020-09-09. Available in PDF, EPUB and Kindle. Book excerpt: Nature-Inspired Optimization Algorithms, Second Edition provides an introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning and control, and multi-objective optimization. This book can serve as an introductory book for graduates, for lecturers in computer science, engineering and natural sciences, and as a source of inspiration for new applications. Discusses and summarizes the latest developments in nature-inspired algorithms with comprehensive, timely literature Provides a theoretical understanding and practical implementation hints Presents a step-by-step introduction to each algorithm Includes four new chapters covering mathematical foundations, techniques for solving discrete and combination optimization problems, data mining techniques and their links to optimization algorithms, and the latest deep learning techniques, background and various applications

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