Metaheuristic Optimization Nature Inspired Algorithms Swarm And Computational Intelligence Theory And Applications

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

Modestus O. Okwu,Lagouge K. Tartibu
Metaheuristic Optimization Nature Inspired Algorithms Swarm and Computational Intelligence Theory and Applications Book PDF

Author : Modestus O. Okwu,Lagouge K. Tartibu
Publisher : Springer Nature
Page : 192 pages
File Size : 42,8 Mb
Release : 2020-11-13
Category : Technology & Engineering
ISBN : 9783030611118

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Metaheuristic Optimization: Nature-Inspired Algorithms Swarm and Computational Intelligence, Theory and Applications by Modestus O. Okwu,Lagouge K. Tartibu Pdf

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 Computation and Swarm Intelligence

Xin-She Yang
Nature Inspired Computation and Swarm Intelligence Book PDF

Author : Xin-She Yang
Publisher : Academic Press
Page : 442 pages
File Size : 51,8 Mb
Release : 2020-04-24
Category : Computers
ISBN : 9780128197141

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Nature-Inspired Computation and Swarm Intelligence by Xin-She Yang Pdf

Nature-inspired computation and swarm intelligence have become popular and effective tools for solving problems in optimization, computational intelligence, soft computing and data science. Recently, the literature in the field has expanded rapidly, with new algorithms and applications emerging. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is a timely reference giving a comprehensive review of relevant state-of-the-art developments in algorithms, theory and applications of nature-inspired algorithms and swarm intelligence. It reviews and documents the new developments, focusing on nature-inspired algorithms and their theoretical analysis, as well as providing a guide to their implementation. The book includes case studies of diverse real-world applications, balancing explanation of the theory with practical implementation. Nature-Inspired Computation and Swarm Intelligence: Algorithms, Theory and Applications is suitable for researchers and graduate students in computer science, engineering, data science, and management science, who want a comprehensive review of algorithms, theory and implementation within the fields of nature inspired computation and swarm intelligence. Introduces nature-inspired algorithms and their fundamentals, including: particle swarm optimization, bat algorithm, cuckoo search, firefly algorithm, flower pollination algorithm, differential evolution and genetic algorithms as well as multi-objective optimization algorithms and others Provides a theoretical foundation and analyses of algorithms, including: statistical theory and Markov chain theory on the convergence and stability of algorithms, dynamical system theory, benchmarking of optimization, no-free-lunch theorems, and a generalized mathematical framework Includes a diversity of case studies of real-world applications: feature selection, clustering and classification, tuning of restricted Boltzmann machines, travelling salesman problem, classification of white blood cells, music generation by artificial intelligence, swarm robots, neural networks, engineering designs and others

Nature-Inspired Optimizers

Seyedali Mirjalili,Jin Song Dong,Andrew Lewis
Nature Inspired Optimizers Book PDF

Author : Seyedali Mirjalili,Jin Song Dong,Andrew Lewis
Publisher : Springer
Page : 245 pages
File Size : 45,7 Mb
Release : 2019-02-01
Category : Technology & Engineering
ISBN : 9783030121273

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Nature-Inspired Optimizers by Seyedali Mirjalili,Jin Song Dong,Andrew Lewis Pdf

This book covers the conventional and most recent theories and applications in the area of evolutionary algorithms, swarm intelligence, and meta-heuristics. Each chapter offers a comprehensive description of a specific algorithm, from the mathematical model to its practical application. Different kind of optimization problems are solved in this book, including those related to path planning, image processing, hand gesture detection, among others. All in all, the book offers a tutorial on how to design, adapt, and evaluate evolutionary algorithms. Source codes for most of the proposed techniques have been included as supplementary materials on a dedicated webpage.

Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms

Dash, Sujata,Tripathy, B.K.,Rahman, Atta ur
Handbook of Research on Modeling Analysis and Application of Nature Inspired Metaheuristic Algorithms Book PDF

Author : Dash, Sujata,Tripathy, B.K.,Rahman, Atta ur
Publisher : IGI Global
Page : 538 pages
File Size : 46,7 Mb
Release : 2017-08-10
Category : Computers
ISBN : 9781522528586

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Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms by Dash, Sujata,Tripathy, B.K.,Rahman, Atta ur Pdf

The digital age is ripe with emerging advances and applications in technological innovations. Mimicking the structure of complex systems in nature can provide new ideas on how to organize mechanical and personal systems. The Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms is an essential scholarly resource on current algorithms that have been inspired by the natural world. Featuring coverage on diverse topics such as cellular automata, simulated annealing, genetic programming, and differential evolution, this reference publication is ideal for scientists, biological engineers, academics, students, and researchers that are interested in discovering what models from nature influence the current technology-centric world.

Nature-Inspired Algorithms for Optimisation

Raymond Chiong
Nature Inspired Algorithms for Optimisation Book PDF

Author : Raymond Chiong
Publisher : Springer Science & Business Media
Page : 524 pages
File Size : 41,6 Mb
Release : 2009-04-28
Category : Mathematics
ISBN : 9783642002663

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Nature-Inspired Algorithms for Optimisation by Raymond Chiong Pdf

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.

Metaheuristics for Machine Learning

Kanak Kalita,Narayanan Ganesh,S. Balamurugan
Metaheuristics for Machine Learning Book PDF

Author : Kanak Kalita,Narayanan Ganesh,S. Balamurugan
Publisher : John Wiley & Sons
Page : 272 pages
File Size : 54,6 Mb
Release : 2024-03-28
Category : Computers
ISBN : 9781394233939

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Metaheuristics for Machine Learning by Kanak Kalita,Narayanan Ganesh,S. Balamurugan Pdf

METAHEURISTICS for MACHINE LEARNING The book unlocks the power of nature-inspired optimization in machine learning and presents a comprehensive guide to cutting-edge algorithms, interdisciplinary insights, and real-world applications. The field of metaheuristic optimization algorithms is experiencing rapid growth, both in academic research and industrial applications. These nature-inspired algorithms, which draw on phenomena like evolution, swarm behavior, and neural systems, have shown remarkable efficiency in solving complex optimization problems. With advancements in machine learning and artificial intelligence, the application of metaheuristic optimization techniques has expanded, demonstrating significant potential in optimizing machine learning models, hyperparameter tuning, and feature selection, among other use-cases. In the industrial landscape, these techniques are becoming indispensable for solving real-world problems in sectors ranging from healthcare to cybersecurity and sustainability. Businesses are incorporating metaheuristic optimization into machine learning workflows to improve decision-making, automate processes, and enhance system performance. As the boundaries of what is computationally possible continue to expand, the integration of metaheuristic optimization and machine learning represents a pioneering frontier in computational intelligence, making this book a timely resource for anyone involved in this interdisciplinary field. Metaheuristics for Machine Learning: Algorithms and Applications serves as a comprehensive guide to the intersection of nature-inspired optimization and machine learning. Authored by leading experts, this book seamlessly integrates insights from computer science, biology, and mathematics to offer a panoramic view of the latest advancements in metaheuristic algorithms. You’ll find detailed yet accessible discussions of algorithmic theory alongside real-world case studies that demonstrate their practical applications in machine learning optimization. Perfect for researchers, practitioners, and students, this book provides cutting-edge content with a focus on applicability and interdisciplinary knowledge. Whether you aim to optimize complex systems, delve into neural networks, or enhance predictive modeling, this book arms you with the tools and understanding you need to tackle challenges efficiently. Equip yourself with this essential resource and navigate the ever-evolving landscape of machine learning and optimization with confidence. Audience The book is aimed at a broad audience encompassing researchers, practitioners, and students in the fields of computer science, data science, engineering, and mathematics. The detailed but accessible content makes it a must-have for both academia and industry professionals interested in the optimization aspects of machine learning algorithms.

Nature-Inspired Algorithms and Applied Optimization

Xin-She Yang
Nature Inspired Algorithms and Applied Optimization Book PDF

Author : Xin-She Yang
Publisher : Springer
Page : 330 pages
File Size : 49,8 Mb
Release : 2017-10-08
Category : Technology & Engineering
ISBN : 9783319676692

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Nature-Inspired Algorithms and Applied Optimization by Xin-She Yang Pdf

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.

Swarm Intelligence and Bio-Inspired Computation

Xin-She Yang,Zhihua Cui,Renbin Xiao,Amir Hossein Gandomi,Mehmet Karamanoglu
Swarm Intelligence and Bio Inspired Computation Book PDF

Author : Xin-She Yang,Zhihua Cui,Renbin Xiao,Amir Hossein Gandomi,Mehmet Karamanoglu
Publisher : Newnes
Page : 450 pages
File Size : 52,9 Mb
Release : 2013-05-16
Category : Computers
ISBN : 9780124051775

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Swarm Intelligence and Bio-Inspired Computation by Xin-She Yang,Zhihua Cui,Renbin Xiao,Amir Hossein Gandomi,Mehmet Karamanoglu Pdf

Swarm Intelligence and bio-inspired computation have become increasing popular in the last two decades. Bio-inspired algorithms such as ant colony algorithms, bat algorithms, bee algorithms, firefly algorithms, cuckoo search and particle swarm optimization have been applied in almost every area of science and engineering with a dramatic increase of number of relevant publications. This book reviews the latest developments in swarm intelligence and bio-inspired computation from both the theory and application side, providing a complete resource that analyzes and discusses the latest and future trends in research directions. It can help new researchers to carry out timely research and inspire readers to develop new algorithms. With its impressive breadth and depth, this book will be useful for advanced undergraduate students, PhD students and lecturers in computer science, engineering and science as well as researchers and engineers. Focuses on the introduction and analysis of key algorithms Includes case studies for real-world applications Contains a balance of theory and applications, so readers who are interested in either algorithm or applications will all benefit from this timely book.

Nature Inspired Cooperative Strategies for Optimization (NICSO 2010)

Carlos Cruz,Juan R. González,David Alejandro Pelta,Natalio Krasnogor,Germán Terrazas
Nature Inspired Cooperative Strategies for Optimization NICSO 2010 Book PDF

Author : Carlos Cruz,Juan R. González,David Alejandro Pelta,Natalio Krasnogor,Germán Terrazas
Publisher : Springer Science & Business Media
Page : 401 pages
File Size : 42,5 Mb
Release : 2010-04-07
Category : Computers
ISBN : 9783642125379

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Nature Inspired Cooperative Strategies for Optimization (NICSO 2010) by Carlos Cruz,Juan R. González,David Alejandro Pelta,Natalio Krasnogor,Germán Terrazas Pdf

Many aspects of Nature, Biology or even from Society have become part of the techniques and algorithms used in computer science or they have been used to enhance or hybridize several techniques through the inclusion of advanced evolution, cooperation or biologically based additions. The previous NICSO workshops were held in Granada, Spain, 2006, Acireale, Italy, 2007, and in Tenerife, Spain, 2008. As in the previous editions, NICSO 2010, held in Granada, Spain, was conceived as a forum for the latest ideas and the state of the art research related to nature inspired cooperative strategies. The contributions collected in this book cover topics including nature-inspired techniques like Genetic Algorithms, Evolutionary Algorithms, Ant and Bee Colonies, Swarm Intelligence approaches, Neural Networks, several Cooperation Models, Structures and Strategies, Agents Models, Social Interactions, as well as new algorithms based on the behaviour of fireflies or bats.

Fuzzy Logic Augmentation of Nature-Inspired Optimization Metaheuristics

Oscar Castillo,Patricia Melin
Fuzzy Logic Augmentation of Nature Inspired Optimization Metaheuristics Book PDF

Author : Oscar Castillo,Patricia Melin
Publisher : Springer
Page : 195 pages
File Size : 40,9 Mb
Release : 2014-09-20
Category : Technology & Engineering
ISBN : 9783319109602

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Fuzzy Logic Augmentation of Nature-Inspired Optimization Metaheuristics by Oscar Castillo,Patricia Melin Pdf

This book describes recent advances on fuzzy logic augmentation of nature-inspired optimization metaheuristics and their application in areas such as intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. The book is organized in two main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of theoretical aspects of fuzzy logic augmentation of nature-inspired optimization metaheuristics, which basically consists of papers that propose new optimization algorithms enhanced using fuzzy systems. The second part contains papers with the main theme of application of optimization algorithms, which are basically papers using nature-inspired techniques to achieve optimization of complex optimization problems in diverse areas of application.

Advanced Optimization by Nature-Inspired Algorithms

Omid Bozorg-Haddad
Advanced Optimization by Nature Inspired Algorithms Book PDF

Author : Omid Bozorg-Haddad
Publisher : Springer
Page : 159 pages
File Size : 41,7 Mb
Release : 2017-06-30
Category : Technology & Engineering
ISBN : 9789811052217

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Advanced Optimization by Nature-Inspired Algorithms by Omid Bozorg-Haddad Pdf

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.

Metaheuristic and Evolutionary Computation: Algorithms and Applications

Hasmat Malik,Atif Iqbal,Puneet Joshi,Sanjay Agrawal,Farhad Ilahi Bakhsh
Metaheuristic and Evolutionary Computation Algorithms and Applications Book PDF

Author : Hasmat Malik,Atif Iqbal,Puneet Joshi,Sanjay Agrawal,Farhad Ilahi Bakhsh
Publisher : Springer Nature
Page : 830 pages
File Size : 42,5 Mb
Release : 2020-10-08
Category : Technology & Engineering
ISBN : 9789811575716

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Metaheuristic and Evolutionary Computation: Algorithms and Applications by Hasmat Malik,Atif Iqbal,Puneet Joshi,Sanjay Agrawal,Farhad Ilahi Bakhsh Pdf

This book addresses the principles and applications of metaheuristic approaches in engineering and related fields. The first part covers metaheuristics tools and techniques such as ant colony optimization and Tabu search, and their applications to several classes of optimization problems. In turn, the book’s second part focuses on a wide variety of metaheuristics applications in engineering and/or the applied sciences, e.g. in smart grids and renewable energy. In addition, the simulation codes for the problems discussed are included in an appendix for ready reference. Intended for researchers aspiring to learn and apply metaheuristic techniques, and gathering contributions by prominent experts in the field, the book offers readers an essential introduction to metaheuristics, its theoretical aspects and applications.

Recent Advances in Swarm Intelligence and Evolutionary Computation

Xin-She Yang
Recent Advances in Swarm Intelligence and Evolutionary Computation Book PDF

Author : Xin-She Yang
Publisher : Springer
Page : 300 pages
File Size : 50,6 Mb
Release : 2014-12-27
Category : Technology & Engineering
ISBN : 9783319138268

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Recent Advances in Swarm Intelligence and Evolutionary Computation by Xin-She Yang Pdf

This timely review volume summarizes the state-of-the-art developments in nature-inspired algorithms and applications with the emphasis on swarm intelligence and bio-inspired computation. Topics include the analysis and overview of swarm intelligence and evolutionary computation, hybrid metaheuristic algorithms, bat algorithm, discrete cuckoo search, firefly algorithm, particle swarm optimization, and harmony search as well as convergent hybridization. Application case studies have focused on the dehydration of fruits and vegetables by the firefly algorithm and goal programming, feature selection by the binary flower pollination algorithm, job shop scheduling, single row facility layout optimization, training of feed-forward neural networks, damage and stiffness identification, synthesis of cross-ambiguity functions by the bat algorithm, web document clustering, truss analysis, water distribution networks, sustainable building designs and others. As a timely review, this book can serve as an ideal reference for graduates, lecturers, engineers and researchers in computer science, evolutionary computing, artificial intelligence, machine learning, computational intelligence, data mining, engineering optimization and designs.

Nature-Inspired Optimization Algorithms

Xin-She Yang
Nature Inspired Optimization Algorithms Book PDF

Author : Xin-She Yang
Publisher : Elsevier
Page : 300 pages
File Size : 41,9 Mb
Release : 2014-02-17
Category : Computers
ISBN : 9780124167452

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Nature-Inspired Optimization Algorithms by Xin-She Yang Pdf

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 and Applied Optimization

Xin-She Yang
Nature Inspired Algorithms and Applied Optimization Book PDF

Author : Xin-She Yang
Publisher : Springer
Page : 0 pages
File Size : 53,5 Mb
Release : 2018-08-15
Category : Technology & Engineering
ISBN : 3319884654

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Nature-Inspired Algorithms and Applied Optimization by Xin-She Yang Pdf

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.