Metaheuristics for Robotics

Metaheuristics for Robotics PDF Author: Hamouche Oulhadj
Publisher: John Wiley & Sons
ISBN: 1786303809
Category : Computers
Languages : en
Pages : 184

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Book Description
This book is dedicated to the application of metaheuristic optimization in trajectory generation and control issues in robotics. In this area, as in other fields of application, the algorithmic tools addressed do not require a comprehensive list of eligible solutions to effectively solve an optimization problem. This book investigates how, by reformulating the problems to be solved, it is possible to obtain results by means of metaheuristics. Through concrete examples and case studies particularly related to robotics this book outlines the essentials of what is needed to reformulate control laws into concrete optimization data. The resolution approaches implemented as well as the results obtained are described in detail, in order to give, as much as possible, an idea of metaheuristics and their performance within the context of their application to robotics.

Metaheuristics for Robotics

Metaheuristics for Robotics PDF Author: Hamouche Oulhadj
Publisher: John Wiley & Sons
ISBN: 1786303809
Category : Computers
Languages : en
Pages : 184

Get Book Here

Book Description
This book is dedicated to the application of metaheuristic optimization in trajectory generation and control issues in robotics. In this area, as in other fields of application, the algorithmic tools addressed do not require a comprehensive list of eligible solutions to effectively solve an optimization problem. This book investigates how, by reformulating the problems to be solved, it is possible to obtain results by means of metaheuristics. Through concrete examples and case studies particularly related to robotics this book outlines the essentials of what is needed to reformulate control laws into concrete optimization data. The resolution approaches implemented as well as the results obtained are described in detail, in order to give, as much as possible, an idea of metaheuristics and their performance within the context of their application to robotics.

Essentials of Metaheuristics (Second Edition)

Essentials of Metaheuristics (Second Edition) PDF Author: Sean Luke
Publisher:
ISBN: 9781300549628
Category : Algorithms
Languages : en
Pages : 242

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Book Description
Interested in the Genetic Algorithm? Simulated Annealing? Ant Colony Optimization? Essentials of Metaheuristics covers these and other metaheuristics algorithms, and is intended for undergraduate students, programmers, and non-experts. The book covers a wide range of algorithms, representations, selection and modification operators, and related topics, and includes 71 figures and 135 algorithms great and small. Algorithms include: Gradient Ascent techniques, Hill-Climbing variants, Simulated Annealing, Tabu Search variants, Iterated Local Search, Evolution Strategies, the Genetic Algorithm, the Steady-State Genetic Algorithm, Differential Evolution, Particle Swarm Optimization, Genetic Programming variants, One- and Two-Population Competitive Coevolution, N-Population Cooperative Coevolution, Implicit Fitness Sharing, Deterministic Crowding, NSGA-II, SPEA2, GRASP, Ant Colony Optimization variants, Guided Local Search, LEM, PBIL, UMDA, cGA, BOA, SAMUEL, ZCS, XCS, and XCSF.

Metaheuristics in Machine Learning: Theory and Applications

Metaheuristics in Machine Learning: Theory and Applications PDF Author: Diego Oliva
Publisher: Springer Nature
ISBN: 3030705420
Category : Computational intelligence
Languages : en
Pages : 765

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Book Description
This book is a collection of the most recent approaches that combine metaheuristics and machine learning. Some of the methods considered in this book are evolutionary, swarm, machine learning, and deep learning. The chapters were classified based on the content; then, the sections are thematic. Different applications and implementations are included; in this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and is useful in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the book is useful for research from the evolutionary computation, artificial intelligence, and image processing communities.

Metaheuristic Algorithms in Industry 4.0

Metaheuristic Algorithms in Industry 4.0 PDF Author: Pritesh Shah
Publisher: CRC Press
ISBN: 1000435989
Category : Computers
Languages : en
Pages : 302

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Book Description
Due to increasing industry 4.0 practices, massive industrial process data is now available for researchers for modelling and optimization. Artificial Intelligence methods can be applied to the ever-increasing process data to achieve robust control against foreseen and unforeseen system fluctuations. Smart computing techniques, machine learning, deep learning, computer vision, for example, will be inseparable from the highly automated factories of tomorrow. Effective cybersecurity will be a must for all Internet of Things (IoT) enabled work and office spaces. This book addresses metaheuristics in all aspects of Industry 4.0. It covers metaheuristic applications in IoT, cyber physical systems, control systems, smart computing, artificial intelligence, sensor networks, robotics, cybersecurity, smart factory, predictive analytics and more. Key features: Includes industrial case studies. Includes chapters on cyber physical systems, machine learning, deep learning, cybersecurity, robotics, smart manufacturing and predictive analytics. surveys current trends and challenges in metaheuristics and industry 4.0. Metaheuristic Algorithms in Industry 4.0 provides a guiding light to engineers, researchers, students, faculty and other professionals engaged in exploring and implementing industry 4.0 solutions in various systems and processes.

Nature-Inspired Methods for Metaheuristics Optimization

Nature-Inspired Methods for Metaheuristics Optimization PDF Author: Fouad Bennis
Publisher: Springer Nature
ISBN: 3030264580
Category : Business & Economics
Languages : en
Pages : 503

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Book Description
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.

Meta-heuristic Optimization Techniques

Meta-heuristic Optimization Techniques PDF Author: Anuj Kumar
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110716259
Category : Computers
Languages : en
Pages : 219

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Book Description
This book offers a thorough overview of the most popular and researched meta-heuristic optimization techniques and nature-inspired algorithms. Their wide applicability makes them a hot research topic and an effi cient tool for the solution of complex optimization problems in various fi elds of sciences, engineering, and in numerous industries.

Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance

Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance PDF Author: Vasant, Pandian M.
Publisher: IGI Global
ISBN: 1466620870
Category : Computers
Languages : en
Pages : 735

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Book Description
Optimization techniques have developed into a significant area concerning industrial, economics, business, and financial systems. With the development of engineering and financial systems, modern optimization has played an important role in service-centered operations and as such has attracted more attention to this field. Meta-heuristic hybrid optimization is a newly development mathematical framework based optimization technique. Designed by logicians, engineers, analysts, and many more, this technique aims to study the complexity of algorithms and problems. Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance explores the emerging study of meta-heuristics optimization algorithms and methods and their role in innovated real world practical applications. This book is a collection of research on the areas of meta-heuristics optimization algorithms in engineering, business, economics, and finance and aims to be a comprehensive reference for decision makers, managers, engineers, researchers, scientists, financiers, and economists as well as industrialists.

Metaheuristics for Hard Optimization

Metaheuristics for Hard Optimization PDF Author: Johann Dréo
Publisher: Springer Science & Business Media
ISBN: 3540309667
Category : Mathematics
Languages : en
Pages : 373

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Book Description
Contains case studies from engineering and operations research Includes commented literature for each chapter

Metaheuristics for Robotics

Metaheuristics for Robotics PDF Author: Hamouche Oulhadj
Publisher: John Wiley & Sons
ISBN: 111970698X
Category : Computers
Languages : en
Pages : 190

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Book Description
This book is dedicated to the application of metaheuristic optimization in trajectory generation and control issues in robotics. In this area, as in other fields of application, the algorithmic tools addressed do not require a comprehensive list of eligible solutions to effectively solve an optimization problem. This book investigates how, by reformulating the problems to be solved, it is possible to obtain results by means of metaheuristics. Through concrete examples and case studies particularly related to robotics this book outlines the essentials of what is needed to reformulate control laws into concrete optimization data. The resolution approaches implemented as well as the results obtained are described in detail, in order to give, as much as possible, an idea of metaheuristics and their performance within the context of their application to robotics.

A New Meta-heuristic Optimization Algorithm Based on the String Theory Paradigm from Physics

A New Meta-heuristic Optimization Algorithm Based on the String Theory Paradigm from Physics PDF Author: Oscar Castillo
Publisher: Springer Nature
ISBN: 3030822885
Category : Technology & Engineering
Languages : en
Pages : 76

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Book Description
This book focuses on the fields of nature-inspired algorithms, optimization problems and fuzzy logic. In this book, a new metaheuristic based on String Theory from Physics is proposed. It is important to mention that we have proposed the new algorithm to generate new potential solutions in optimization problems in order to find new ways that could improve the results in solving these problems. We are presenting the results for the proposed method in different cases of study. The first case, is optimization of traditional benchmark mathematical functions. The second case, is the optimization of benchmark functions of the CEC 2015 Competition and we are also presenting results of the CEC 2017 Competition on Constrained Real-Parameter Optimization that are problems that contain the presence of constraints that alter the shape of the search space making them more difficult to solve. Finally, in the third case, we are presenting the optimization of a fuzzy inference system, specifically for finding the optimal design of a fuzzy controller for an autonomous mobile robot. It is important to mention that in all study cases we are presenting statistical tests in or-der to validate the performance of proposed method. In summary, we believe that this book will be of great interest to a wide audience, ranging from engineering and science graduate students, to researchers and professors in computational intelligence, metaheuristics, optimization, robotics and control.