Nature Inspired Algorithms And Applied Optimization eBook Download PDF

Download Nature Inspired Algorithms And Applied Optimization full books in PDF, epub, and Kindle. Read online Nature Inspired Algorithms And Applied Optimization ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Nature-Inspired Algorithms and Applied Optimization

Author: Xin-She Yang

Publisher: Springer

Published: 2017-10-08

Total Pages: 330

ISBN-13: 3319676695

DOWNLOAD EBOOK

This book reviews the state-of-the-art developments in nature-inspired algorithms and their applications in various disciplines, ranging from feature selection and engineering design optimization to scheduling and vehicle routing. It introduces each algorithm and its implementation with case studies as well as extensive literature reviews, and also includes self-contained chapters featuring theoretical analyses, such as convergence analysis and no-free-lunch theorems so as to provide insights into the current nature-inspired optimization algorithms. Topics include ant colony optimization, the bat algorithm, B-spline curve fitting, cuckoo search, feature selection, economic load dispatch, the firefly algorithm, the flower pollination algorithm, knapsack problem, octonian and quaternion representations, particle swarm optimization, scheduling, wireless networks, vehicle routing with time windows, and maximally different alternatives. This timely book serves as a practical guide and reference resource for students, researchers and professionals.

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

Download or read book Nature-Inspired Algorithms and Applied Optimization written by Xin-She Yang and published by Springer. This book was released on 2017-10-08 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the state-of-the-art developments in nature-inspired algorithms and their applications in various disciplines, ranging from feature selection and engineering design optimization to scheduling and vehicle routing. It introduces each algorithm and its implementation with case studies as well as extensive literature reviews, and also includes self-contained chapters featuring theoretical analyses, such as convergence analysis and no-free-lunch theorems so as to provide insights into the current nature-inspired optimization algorithms. Topics include ant colony optimization, the bat algorithm, B-spline curve fitting, cuckoo search, feature selection, economic load dispatch, the firefly algorithm, the flower pollination algorithm, knapsack problem, octonian and quaternion representations, particle swarm optimization, scheduling, wireless networks, vehicle routing with time windows, and maximally different alternatives. This timely book serves as a practical guide and reference resource for students, researchers and professionals.

Nature-Inspired Optimization Algorithms

Author: Xin-She Yang

Publisher: Elsevier

Published: 2014-02-17

Total Pages: 277

ISBN-13: 0124167454

DOWNLOAD EBOOK

Nature-Inspired Optimization Algorithms provides a systematic 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 well-chosen 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, as well as multi-objective optimization. This book can serve as an introductory book for graduates, doctoral students and lecturers in computer science, engineering and natural sciences. It can also serve a source of inspiration for new applications. Researchers and engineers as well as experienced experts will also find it a handy reference. Discusses and summarizes the latest developments in nature-inspired algorithms with comprehensive, timely literature Provides a theoretical understanding as well as practical implementation hints Provides a step-by-step introduction to each algorithm

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

Download or read book Nature-Inspired Optimization Algorithms written by Xin-She Yang and published by Elsevier. This book was released on 2014-02-17 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nature-Inspired Optimization Algorithms provides a systematic 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 well-chosen 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, as well as multi-objective optimization. This book can serve as an introductory book for graduates, doctoral students and lecturers in computer science, engineering and natural sciences. It can also serve a source of inspiration for new applications. Researchers and engineers as well as experienced experts will also find it a handy reference. Discusses and summarizes the latest developments in nature-inspired algorithms with comprehensive, timely literature Provides a theoretical understanding as well as practical implementation hints Provides a step-by-step introduction to each algorithm

Nature-Inspired Algorithms for Optimisation

Author: Raymond Chiong

Publisher: Springer

Published: 2009-05-02

Total Pages: 524

ISBN-13: 3642002676

DOWNLOAD EBOOK

Nature-Inspired Algorithms have been gaining much popularity in recent years due to the fact that many real-world optimisation problems have become increasingly large, complex and dynamic. The size and complexity of the problems nowadays require the development of methods and solutions whose efficiency is measured by their ability to find acceptable results within a reasonable amount of time, rather than an ability to guarantee the optimal solution. This volume 'Nature-Inspired Algorithms for Optimisation' is a collection of the latest state-of-the-art algorithms and important studies for tackling various kinds of optimisation problems. It comprises 18 chapters, including two introductory chapters which address the fundamental issues that have made optimisation problems difficult to solve and explain the rationale for seeking inspiration from nature. The contributions stand out through their novelty and clarity of the algorithmic descriptions and analyses, and lead the way to interesting and varied new applications.

Book Synopsis Nature-Inspired Algorithms for Optimisation by : Raymond Chiong

Download or read book Nature-Inspired Algorithms for Optimisation written by Raymond Chiong and published by Springer. This book was released on 2009-05-02 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nature-Inspired Algorithms have been gaining much popularity in recent years due to the fact that many real-world optimisation problems have become increasingly large, complex and dynamic. The size and complexity of the problems nowadays require the development of methods and solutions whose efficiency is measured by their ability to find acceptable results within a reasonable amount of time, rather than an ability to guarantee the optimal solution. This volume 'Nature-Inspired Algorithms for Optimisation' is a collection of the latest state-of-the-art algorithms and important studies for tackling various kinds of optimisation problems. It comprises 18 chapters, including two introductory chapters which address the fundamental issues that have made optimisation problems difficult to solve and explain the rationale for seeking inspiration from nature. The contributions stand out through their novelty and clarity of the algorithmic descriptions and analyses, and lead the way to interesting and varied new applications.

Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications

Author: Modestus O. Okwu

Publisher: Springer Nature

Published: 2020-11-13

Total Pages: 192

ISBN-13: 3030611116

DOWNLOAD EBOOK

This book exemplifies how algorithms are developed by mimicking nature. Classical techniques for solving day-to-day problems is time-consuming and cannot address complex problems. Metaheuristic algorithms are nature-inspired optimization techniques for solving real-life complex problems. This book emphasizes the social behaviour of insects, animals and other natural entities, in terms of converging power and benefits. Major nature-inspired algorithms discussed in this book include the bee colony algorithm, ant colony algorithm, grey wolf optimization algorithm, whale optimization algorithm, firefly algorithm, bat algorithm, ant lion optimization algorithm, grasshopper optimization algorithm, butterfly optimization algorithm and others. The algorithms have been arranged in chapters to help readers gain better insight into nature-inspired systems and swarm intelligence. All the MATLAB codes have been provided in the appendices of the book to enable readers practice how to solve examples included in all sections. This book is for experts in Engineering and Applied Sciences, Natural and Formal Sciences, Economics, Humanities and Social Sciences.

Book Synopsis Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications by : Modestus O. Okwu

Download or read book Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications written by Modestus O. Okwu and published by Springer Nature. This book was released on 2020-11-13 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book exemplifies how algorithms are developed by mimicking nature. Classical techniques for solving day-to-day problems is time-consuming and cannot address complex problems. Metaheuristic algorithms are nature-inspired optimization techniques for solving real-life complex problems. This book emphasizes the social behaviour of insects, animals and other natural entities, in terms of converging power and benefits. Major nature-inspired algorithms discussed in this book include the bee colony algorithm, ant colony algorithm, grey wolf optimization algorithm, whale optimization algorithm, firefly algorithm, bat algorithm, ant lion optimization algorithm, grasshopper optimization algorithm, butterfly optimization algorithm and others. The algorithms have been arranged in chapters to help readers gain better insight into nature-inspired systems and swarm intelligence. All the MATLAB codes have been provided in the appendices of the book to enable readers practice how to solve examples included in all sections. This book is for experts in Engineering and Applied Sciences, Natural and Formal Sciences, Economics, Humanities and Social Sciences.

Nature-Inspired Algorithms and Applications

Author: S. Balamurugan

Publisher: John Wiley & Sons

Published: 2021-12-14

Total Pages: 388

ISBN-13: 111968174X

DOWNLOAD EBOOK

NATURE-INSPIRED ALGORITHMS AND APPLICATIONS The book’s unified approach of balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Inspired by the world around them, researchers are gathering information that can be developed for use in areas where certain practical applications of nature-inspired computation and machine learning can be applied. This book is designed to enhance the reader’s understanding of this process by portraying certain practical applications of nature-inspired algorithms (NIAs) specifically designed to solve complex real-world problems in data analytics and pattern recognition by means of domain-specific solutions. Since various NIAs and their multidisciplinary applications in the mechanical engineering and electrical engineering sectors; and in machine learning, image processing, data mining, and wireless networks are dealt with in detail in this book, it can act as a handy reference guide. Among the subjects of the 12 chapters are: A novel method based on TRIZ to map real-world problems to nature problems Applications of cuckoo search algorithm for optimization problems Performance analysis of nature-inspired algorithms in breast cancer diagnosis Nature-inspired computation in data mining Hybrid bat-genetic algorithm–based novel optimal wavelet filter for compression of image data Efficiency of finding best solutions through ant colony optimization techniques Applications of hybridized algorithms and novel algorithms in the field of machine learning. Audience: Researchers and graduate students in mechanical engineering, electrical engineering, machine learning, image processing, data mining, and wireless networks will find this book very useful.

Book Synopsis Nature-Inspired Algorithms and Applications by : S. Balamurugan

Download or read book Nature-Inspired Algorithms and Applications written by S. Balamurugan and published by John Wiley & Sons. This book was released on 2021-12-14 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: NATURE-INSPIRED ALGORITHMS AND APPLICATIONS The book’s unified approach of balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Inspired by the world around them, researchers are gathering information that can be developed for use in areas where certain practical applications of nature-inspired computation and machine learning can be applied. This book is designed to enhance the reader’s understanding of this process by portraying certain practical applications of nature-inspired algorithms (NIAs) specifically designed to solve complex real-world problems in data analytics and pattern recognition by means of domain-specific solutions. Since various NIAs and their multidisciplinary applications in the mechanical engineering and electrical engineering sectors; and in machine learning, image processing, data mining, and wireless networks are dealt with in detail in this book, it can act as a handy reference guide. Among the subjects of the 12 chapters are: A novel method based on TRIZ to map real-world problems to nature problems Applications of cuckoo search algorithm for optimization problems Performance analysis of nature-inspired algorithms in breast cancer diagnosis Nature-inspired computation in data mining Hybrid bat-genetic algorithm–based novel optimal wavelet filter for compression of image data Efficiency of finding best solutions through ant colony optimization techniques Applications of hybridized algorithms and novel algorithms in the field of machine learning. Audience: Researchers and graduate students in mechanical engineering, electrical engineering, machine learning, image processing, data mining, and wireless networks will find this book very useful.

Applied Optimization and Swarm Intelligence

Author: Eneko Osaba

Publisher: Springer Nature

Published: 2021-05-17

Total Pages: 236

ISBN-13: 9811606625

DOWNLOAD EBOOK

This book gravitates on the prominent theories and recent developments of swarm intelligence methods, and their application in both synthetic and real-world optimization problems. The special interest will be placed in those algorithmic variants where biological processes observed in nature have underpinned the core operators underlying their search mechanisms. In other words, the book centers its attention on swarm intelligence and nature-inspired methods for efficient optimization and problem solving. The content of this book unleashes a great opportunity for researchers, lecturers and practitioners interested in swarm intelligence, optimization problems and artificial intelligence.

Book Synopsis Applied Optimization and Swarm Intelligence by : Eneko Osaba

Download or read book Applied Optimization and Swarm Intelligence written by Eneko Osaba and published by Springer Nature. This book was released on 2021-05-17 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gravitates on the prominent theories and recent developments of swarm intelligence methods, and their application in both synthetic and real-world optimization problems. The special interest will be placed in those algorithmic variants where biological processes observed in nature have underpinned the core operators underlying their search mechanisms. In other words, the book centers its attention on swarm intelligence and nature-inspired methods for efficient optimization and problem solving. The content of this book unleashes a great opportunity for researchers, lecturers and practitioners interested in swarm intelligence, optimization problems and artificial intelligence.

Advanced Optimization by Nature-Inspired Algorithms

Author: Omid Bozorg-Haddad

Publisher: Springer

Published: 2017-06-30

Total Pages: 159

ISBN-13: 9811052212

DOWNLOAD EBOOK

This book, compiles, presents, and explains the most important meta-heuristic and evolutionary optimization algorithms whose successful performance has been proven in different fields of engineering, and it includes application of these algorithms to important engineering optimization problems. In addition, this book guides readers to studies that have implemented these algorithms by providing a literature review on developments and applications of each algorithm. This book is intended for students, but can be used by researchers and professionals in the area of engineering optimization.

Book Synopsis Advanced Optimization by Nature-Inspired Algorithms by : Omid Bozorg-Haddad

Download or read book Advanced Optimization by Nature-Inspired Algorithms written by Omid Bozorg-Haddad and published by Springer. This book was released on 2017-06-30 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, compiles, presents, and explains the most important meta-heuristic and evolutionary optimization algorithms whose successful performance has been proven in different fields of engineering, and it includes application of these algorithms to important engineering optimization problems. In addition, this book guides readers to studies that have implemented these algorithms by providing a literature review on developments and applications of each algorithm. This book is intended for students, but can be used by researchers and professionals in the area of engineering optimization.

Introduction to Nature-Inspired Optimization

Author: George Lindfield

Publisher: Academic Press

Published: 2017-08-10

Total Pages: 256

ISBN-13: 0128036664

DOWNLOAD EBOOK

Introduction to Nature-Inspired Optimization brings together many of the innovative mathematical methods for non-linear optimization that have their origins in the way various species behave in order to optimize their chances of survival. The book describes each method, examines their strengths and weaknesses, and where appropriate, provides the MATLAB code to give practical insight into the detailed structure of these methods and how they work. Nature-inspired algorithms emulate processes that are found in the natural world, spurring interest for optimization. Lindfield/Penny provide concise coverage to all the major algorithms, including genetic algorithms, artificial bee colony algorithms, ant colony optimization and the cuckoo search algorithm, among others. This book provides a quick reference to practicing engineers, researchers and graduate students who work in the field of optimization. Applies concepts in nature and biology to develop new algorithms for nonlinear optimization Offers working MATLAB® programs for the major algorithms described, applying them to a range of problems Provides useful comparative studies of the algorithms, highlighting their strengths and weaknesses Discusses the current state-of-the-field and indicates possible areas of future development

Book Synopsis Introduction to Nature-Inspired Optimization by : George Lindfield

Download or read book Introduction to Nature-Inspired Optimization written by George Lindfield and published by Academic Press. This book was released on 2017-08-10 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Nature-Inspired Optimization brings together many of the innovative mathematical methods for non-linear optimization that have their origins in the way various species behave in order to optimize their chances of survival. The book describes each method, examines their strengths and weaknesses, and where appropriate, provides the MATLAB code to give practical insight into the detailed structure of these methods and how they work. Nature-inspired algorithms emulate processes that are found in the natural world, spurring interest for optimization. Lindfield/Penny provide concise coverage to all the major algorithms, including genetic algorithms, artificial bee colony algorithms, ant colony optimization and the cuckoo search algorithm, among others. This book provides a quick reference to practicing engineers, researchers and graduate students who work in the field of optimization. Applies concepts in nature and biology to develop new algorithms for nonlinear optimization Offers working MATLAB® programs for the major algorithms described, applying them to a range of problems Provides useful comparative studies of the algorithms, highlighting their strengths and weaknesses Discusses the current state-of-the-field and indicates possible areas of future development

Nature-Inspired Methods for Metaheuristics Optimization

Author: Fouad Bennis

Publisher: Springer Nature

Published: 2020-01-17

Total Pages: 503

ISBN-13: 3030264580

DOWNLOAD EBOOK

This book gathers together a set of chapters covering recent development in optimization methods that are inspired by nature. The first group of chapters describes in detail different meta-heuristic algorithms, and shows their applicability using some test or real-world problems. The second part of the book is especially focused on advanced applications and case studies. They span different engineering fields, including mechanical, electrical and civil engineering, and earth/environmental science, and covers topics such as robotics, water management, process optimization, among others. The book covers both basic concepts and advanced issues, offering a timely introduction to nature-inspired optimization method for newcomers and students, and a source of inspiration as well as important practical insights to engineers and researchers.

Book Synopsis Nature-Inspired Methods for Metaheuristics Optimization by : Fouad Bennis

Download or read book Nature-Inspired Methods for Metaheuristics Optimization written by Fouad Bennis and published by Springer Nature. This book was released on 2020-01-17 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers together a set of chapters covering recent development in optimization methods that are inspired by nature. The first group of chapters describes in detail different meta-heuristic algorithms, and shows their applicability using some test or real-world problems. The second part of the book is especially focused on advanced applications and case studies. They span different engineering fields, including mechanical, electrical and civil engineering, and earth/environmental science, and covers topics such as robotics, water management, process optimization, among others. The book covers both basic concepts and advanced issues, offering a timely introduction to nature-inspired optimization method for newcomers and students, and a source of inspiration as well as important practical insights to engineers and researchers.

Nature-inspired Metaheuristic Algorithms

Author: Xin-She Yang

Publisher: Luniver Press

Published: 2010

Total Pages: 148

ISBN-13: 1905986289

DOWNLOAD EBOOK

Modern metaheuristic algorithms such as bee algorithms and harmony search start to demonstrate their power in dealing with tough optimization problems and even NP-hard problems. This book reviews and introduces the state-of-the-art nature-inspired metaheuristic algorithms in optimization, including genetic algorithms, bee algorithms, particle swarm optimization, simulated annealing, ant colony optimization, harmony search, and firefly algorithms. We also briefly introduce the photosynthetic algorithm, the enzyme algorithm, and Tabu search. Worked examples with implementation have been used to show how each algorithm works. This book is thus an ideal textbook for an undergraduate and/or graduate course. As some of the algorithms such as the harmony search and firefly algorithms are at the forefront of current research, this book can also serve as a reference book for researchers.

Book Synopsis Nature-inspired Metaheuristic Algorithms by : Xin-She Yang

Download or read book Nature-inspired Metaheuristic Algorithms written by Xin-She Yang and published by Luniver Press. This book was released on 2010 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern metaheuristic algorithms such as bee algorithms and harmony search start to demonstrate their power in dealing with tough optimization problems and even NP-hard problems. This book reviews and introduces the state-of-the-art nature-inspired metaheuristic algorithms in optimization, including genetic algorithms, bee algorithms, particle swarm optimization, simulated annealing, ant colony optimization, harmony search, and firefly algorithms. We also briefly introduce the photosynthetic algorithm, the enzyme algorithm, and Tabu search. Worked examples with implementation have been used to show how each algorithm works. This book is thus an ideal textbook for an undergraduate and/or graduate course. As some of the algorithms such as the harmony search and firefly algorithms are at the forefront of current research, this book can also serve as a reference book for researchers.