Metaheuristic Computation: A Performance Perspective

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Author :
Publisher : Springer Nature
ISBN 13 : 3030581004
Total Pages : 281 pages
Book Rating : 4.08/5 ( download)

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Book Synopsis Metaheuristic Computation: A Performance Perspective by : Erik Cuevas

Download or read book Metaheuristic Computation: A Performance Perspective written by Erik Cuevas and published by Springer Nature. This book was released on 2020-10-05 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is primarily intended for undergraduate and postgraduate students of Science, Electrical Engineering, or Computational Mathematics. Metaheuristic search methods are so numerous and varied in terms of design and potential applications; however, for such an abundant family of optimization techniques, there seems to be a question which needs to be answered: Which part of the design in a metaheuristic algorithm contributes more to its better performance? Several works that compare the performance among metaheuristic approaches have been reported in the literature. Nevertheless, they suffer from one of the following limitations: (A)Their conclusions are based on the performance of popular evolutionary approaches over a set of synthetic functions with exact solutions and well-known behaviors, without considering the application context or including recent developments. (B) Their conclusions consider only the comparison of their final results which cannot evaluate the nature of a good or bad balance between exploration and exploitation. The objective of this book is to compare the performance of various metaheuristic techniques when they are faced with complex optimization problems extracted from different engineering domains. The material has been compiled from a teaching perspective.

Metaheuristic Computation with MATLAB®

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Author :
Publisher : CRC Press
ISBN 13 : 1000096513
Total Pages : 260 pages
Book Rating : 4.14/5 ( download)

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Book Synopsis Metaheuristic Computation with MATLAB® by : Erik Cuevas

Download or read book Metaheuristic Computation with MATLAB® written by Erik Cuevas and published by CRC Press. This book was released on 2020-09-14 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Metaheuristic algorithms are considered as generic optimization tools that can solve very complex problems characterized by having very large search spaces. Metaheuristic methods reduce the effective size of the search space through the use of effective search strategies. Book Features: Provides a unified view of the most popular metaheuristic methods currently in use Includes the necessary concepts to enable readers to implement and modify already known metaheuristic methods to solve problems Covers design aspects and implementation in MATLAB® Contains numerous examples of problems and solutions that demonstrate the power of these methods of optimization The material has been written from a teaching perspective and, for this reason, this book is primarily intended for undergraduate and postgraduate students of artificial intelligence, metaheuristic methods, and/or evolutionary computation. The objective is to bridge the gap between metaheuristic techniques and complex optimization problems that profit from the convenient properties of metaheuristic approaches. Therefore, engineer practitioners who are not familiar with metaheuristic computation will appreciate that the techniques discussed are beyond simple theoretical tools, since they have been adapted to solve significant problems that commonly arise in such areas.

Recent Metaheuristic Computation Schemes in Engineering

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Author :
Publisher : Springer Nature
ISBN 13 : 3030660079
Total Pages : 282 pages
Book Rating : 4.79/5 ( download)

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Book Synopsis Recent Metaheuristic Computation Schemes in Engineering by : Erik Cuevas

Download or read book Recent Metaheuristic Computation Schemes in Engineering written by Erik Cuevas and published by Springer Nature. This book was released on 2021-02-04 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes two objectives. The first goal is to present advances and developments which have proved to be effective in their application to several complex problems. The second objective is to present the performance comparison of various metaheuristic techniques when they face complex optimization problems. The material has been compiled from a teaching perspective. Most of the problems in science, engineering, economics, and other areas can be translated as an optimization or a search problem. According to their characteristics, some problems can be simple that can be solved by traditional optimization methods based on mathematical analysis. However, most of the problems of practical importance in engineering represent complex scenarios so that they are very hard to be solved by using traditional approaches. Under such circumstances, metaheuristic has emerged as the best alternative to solve this kind of complex formulations. This book is primarily intended for undergraduate and postgraduate students. Engineers and application developers can also benefit from the book contents since it has been structured so that each chapter can be read independently from the others, and therefore, only potential interesting information can be quickly available for solving an industrial problem at hand.

Metaheuristic Algorithms: New Methods, Evaluation, and Performance Analysis

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Author :
Publisher : Springer
ISBN 13 : 9783031630521
Total Pages : 0 pages
Book Rating : 4.21/5 ( download)

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Book Synopsis Metaheuristic Algorithms: New Methods, Evaluation, and Performance Analysis by : Erik Cuevas

Download or read book Metaheuristic Algorithms: New Methods, Evaluation, and Performance Analysis written by Erik Cuevas and published by Springer. This book was released on 2024-08-20 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book encompasses three distinct yet interconnected objectives. Firstly, it aims to present and elucidate novel metaheuristic algorithms that feature innovative search mechanisms, setting them apart from conventional metaheuristic methods. Secondly, this book endeavors to systematically assess the performance of well-established algorithms across a spectrum of intricate and real-world problems. Finally, this book serves as a vital resource for the analysis and evaluation of metaheuristic algorithms. It provides a foundational framework for assessing their performance, particularly in terms of the balance between exploration and exploitation, as well as their capacity to obtain optimal solutions. Collectively, these objectives contribute to advancing our understanding of metaheuristic methods and their applicability in addressing diverse and demanding optimization tasks. The materials were compiled from a teaching perspective. For this reason, the book is primarily intended for undergraduate and postgraduate students of Science, Electrical Engineering, or Computational Mathematics. Additionally, engineering practitioners who are not familiar with metaheuristic computation concepts will appreciate that the techniques discussed are beyond simple theoretical tools because they have been adapted to solve significant problems that commonly arise in engineering areas.

New Metaheuristic Schemes: Mechanisms and Applications

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Author :
Publisher : Springer Nature
ISBN 13 : 3031455614
Total Pages : 280 pages
Book Rating : 4.12/5 ( download)

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Book Synopsis New Metaheuristic Schemes: Mechanisms and Applications by : Erik Cuevas

Download or read book New Metaheuristic Schemes: Mechanisms and Applications written by Erik Cuevas and published by Springer Nature. This book was released on 2023-12-08 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, novel metaheuristic techniques have emerged in response to the limitations of conventional approaches, leading to enhanced outcomes. These new methods introduce interesting mechanisms and innovative collaborative strategies that facilitate the efficient exploration and exploitation of extensive search spaces characterized by numerous dimensions. The objective of this book is to present advancements that discuss novel alternative metaheuristic developments that have demonstrated their effectiveness in tackling various complex problems. This book encompasses a variety of emerging metaheuristic methods and their practical applications. The content is presented from a teaching perspective, making it particularly suitable for undergraduate and postgraduate students in fields such as science, electrical engineering, and computational mathematics. The book aligns well with courses in artificial intelligence, electrical engineering, and evolutionary computation. Furthermore, the material offers valuable insights to researchers within the metaheuristic and engineering communities. Similarly, engineering practitioners unfamiliar with metaheuristic computation concepts will recognize the pragmatic value of the discussed techniques. These methods transcend mere theoretical tools that have been adapted to effectively address the significant real-world problems commonly encountered in engineering domains.

Tuning Metaheuristics

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Publisher : Springer Science & Business Media
ISBN 13 : 3642004822
Total Pages : 226 pages
Book Rating : 4.27/5 ( download)

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Book Synopsis Tuning Metaheuristics by : Mauro Birattari

Download or read book Tuning Metaheuristics written by Mauro Birattari and published by Springer Science & Business Media. This book was released on 2009-04-08 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book lays the foundations for a scientific approach to tuning metaheuristics. The fundamental intuition that underlies Birattari's approach is that the tuning problem has much in common with the problems that are typically faced in machine learning.

An Introduction to Metaheuristics for Optimization

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Author :
Publisher : Springer
ISBN 13 : 3319930737
Total Pages : 226 pages
Book Rating : 4.32/5 ( download)

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Book Synopsis An Introduction to Metaheuristics for Optimization by : Bastien Chopard

Download or read book An Introduction to Metaheuristics for Optimization written by Bastien Chopard and published by Springer. This book was released on 2018-11-02 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authors stress the relative simplicity, efficiency, flexibility of use, and suitability of various approaches used to solve difficult optimization problems. The authors are experienced, interdisciplinary lecturers and researchers and in their explanations they demonstrate many shared foundational concepts among the key methodologies. This textbook is a suitable introduction for undergraduate and graduate students, researchers, and professionals in computer science, engineering, and logistics.

Modeling, Analysis, and Applications in Metaheuristic Computing: Advancements and Trends

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Author :
Publisher : IGI Global
ISBN 13 : 1466602716
Total Pages : 446 pages
Book Rating : 4.17/5 ( download)

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Book Synopsis Modeling, Analysis, and Applications in Metaheuristic Computing: Advancements and Trends by : Yin, Peng-Yeng

Download or read book Modeling, Analysis, and Applications in Metaheuristic Computing: Advancements and Trends written by Yin, Peng-Yeng and published by IGI Global. This book was released on 2012-03-31 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is a collection of the latest developments, models, and applications within the transdisciplinary fields related to metaheuristic computing, providing readers with insight into a wide range of topics such as genetic algorithms, differential evolution, and ant colony optimization"--Provided by publisher.

Analysis and Comparison of Metaheuristics

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Author :
Publisher : Springer Nature
ISBN 13 : 3031201051
Total Pages : 230 pages
Book Rating : 4.59/5 ( download)

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Book Synopsis Analysis and Comparison of Metaheuristics by : Erik Cuevas

Download or read book Analysis and Comparison of Metaheuristics written by Erik Cuevas and published by Springer Nature. This book was released on 2022-11-02 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comparative perspective of current metaheuristic developments, which have proved to be effective in their application to several complex problems. The study of biological and social entities such as animals, humans, or insects that manifest a cooperative behavior has produced several computational models in metaheuristic methods. Although these schemes emulate very different processes or systems, the rules used to model individual behavior are very similar. Under such conditions, it is not clear to identify which are the advantages or disadvantages of each metaheuristic technique. The book is compiled from a teaching perspective. For this reason, the book is primarily intended for undergraduate and postgraduate students of Science, Electrical Engineering, or Computational Mathematics. It is appropriate for courses such as Artificial Intelligence, Electrical Engineering, Evolutionary Computation. The book is also useful for researchers from the evolutionary and engineering communities. Likewise, engineer practitioners, who are not familiar with metaheuristic computation concepts, will appreciate that the techniques discussed are beyond simple theoretical tools since they have been adapted to solve significant problems that commonly arise in engineering areas.

Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems

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Author :
Publisher : Springer Nature
ISBN 13 : 3030990796
Total Pages : 501 pages
Book Rating : 4.94/5 ( download)

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Book Synopsis Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems by : Essam Halim Houssein

Download or read book Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems written by Essam Halim Houssein and published by Springer Nature. This book was released on 2022-06-04 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book collects different methodologies that permit metaheuristics and machine learning to solve real-world problems. This book has exciting chapters that employ evolutionary and swarm optimization tools combined with machine learning techniques. The fields of applications are from distribution systems until medical diagnosis, and they are also included different surveys and literature reviews that will enrich the reader. Besides, cutting-edge methods such as neuroevolutionary and IoT implementations are presented in some chapters. 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 can be used in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the material can be helpful for research from the evolutionary computation, artificial intelligence communities.