Advances In Metaheuristics Algorithms Methods And Applications

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Advances in Metaheuristics Algorithms

Author : Erik Cuevas
Publisher :
ISBN 13 : 9783319893105
Total Pages : 218 pages
Book Rating : 4.8/5 (931 download)

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Book Synopsis Advances in Metaheuristics Algorithms by : Erik Cuevas

Download or read book Advances in Metaheuristics Algorithms written by Erik Cuevas and published by . This book was released on 2018 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores new alternative metaheuristic developments that have proved to be effective in their application to several complex problems. Though most of the new metaheuristic algorithms considered offer promising results, they are nevertheless still in their infancy. To grow and attain their full potential, new metaheuristic methods must be applied in a great variety of problems and contexts, so that they not only perform well in their reported sets of optimization problems, but also in new complex formulations. The only way to accomplish this is to disseminate these methods in various technical areas as optimization tools. In general, once a scientist, engineer or practitioner recognizes a problem as a particular instance of a more generic class, he/she can select one of several metaheuristic algorithms that guarantee an expected optimization performance. Unfortunately, the set of options are concentrated on algorithms whose popularity and high proliferation outstrip those of the new developments. This structure is important, because the authors recognize this methodology as the best way to help researchers, lecturers, engineers and practitioners solve their own optimization problems.

Meta-Heuristics

Author : Stefan Voß
Publisher : Springer Science & Business Media
ISBN 13 : 1461557755
Total Pages : 513 pages
Book Rating : 4.4/5 (615 download)

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Book Synopsis Meta-Heuristics by : Stefan Voß

Download or read book Meta-Heuristics written by Stefan Voß and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 513 pages. Available in PDF, EPUB and Kindle. Book excerpt: Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimizations comprises a carefully refereed selection of extended versions of the best papers presented at the Second Meta-Heuristics Conference (MIC 97). The selected articles describe the most recent developments in theory and applications of meta-heuristics, heuristics for specific problems, and comparative case studies. The book is divided into six parts, grouped mainly by the techniques considered. The extensive first part with twelve papers covers tabu search and its application to a great variety of well-known combinatorial optimization problems (including the resource-constrained project scheduling problem and vehicle routing problems). In the second part we find one paper where tabu search and simulated annealing are investigated comparatively and two papers which consider hybrid methods combining tabu search with genetic algorithms. The third part has four papers on genetic and evolutionary algorithms. Part four arrives at a new paradigm within meta-heuristics. The fifth part studies the behavior of parallel local search algorithms mainly from a tabu search perspective. The final part examines a great variety of additional meta-heuristics topics, including neural networks and variable neighbourhood search as well as guided local search. Furthermore, the integration of meta-heuristics with the branch-and-bound paradigm is investigated.

Advances in Metaheuristics for Hard Optimization

Author : Patrick Siarry
Publisher : Springer Science & Business Media
ISBN 13 : 3540729607
Total Pages : 481 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Advances in Metaheuristics for Hard Optimization by : Patrick Siarry

Download or read book Advances in Metaheuristics for Hard Optimization written by Patrick Siarry and published by Springer Science & Business Media. This book was released on 2007-12-06 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many advances have recently been made in metaheuristic methods, from theory to applications. The editors, both leading experts in this field, have assembled a team of researchers to contribute 21 chapters organized into parts on simulated annealing, tabu search, ant colony algorithms, general purpose studies of evolutionary algorithms, applications of evolutionary algorithms, and metaheuristics.

Advances in Metaheuristics Algorithms: Methods and Applications

Author : Erik Cuevas
Publisher : Springer
ISBN 13 : 3319893092
Total Pages : 218 pages
Book Rating : 4.3/5 (198 download)

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Book Synopsis Advances in Metaheuristics Algorithms: Methods and Applications by : Erik Cuevas

Download or read book Advances in Metaheuristics Algorithms: Methods and Applications written by Erik Cuevas and published by Springer. This book was released on 2018-04-10 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores new alternative metaheuristic developments that have proved to be effective in their application to several complex problems. Though most of the new metaheuristic algorithms considered offer promising results, they are nevertheless still in their infancy. To grow and attain their full potential, new metaheuristic methods must be applied in a great variety of problems and contexts, so that they not only perform well in their reported sets of optimization problems, but also in new complex formulations. The only way to accomplish this is to disseminate these methods in various technical areas as optimization tools. In general, once a scientist, engineer or practitioner recognizes a problem as a particular instance of a more generic class, he/she can select one of several metaheuristic algorithms that guarantee an expected optimization performance. Unfortunately, the set of options are concentrated on algorithms whose popularity and high proliferation outstrip those of the new developments. This structure is important, because the authors recognize this methodology as the best way to help researchers, lecturers, engineers and practitioners solve their own optimization problems.

Metaheuristic Algorithms in Industry 4.0

Author : Pritesh Shah
Publisher : CRC Press
ISBN 13 : 1000435989
Total Pages : 302 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Metaheuristic Algorithms in Industry 4.0 by : Pritesh Shah

Download or read book Metaheuristic Algorithms in Industry 4.0 written by Pritesh Shah and published by CRC Press. This book was released on 2021-09-29 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

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

Author : Vasant, Pandian M.
Publisher : IGI Global
ISBN 13 : 1466620870
Total Pages : 735 pages
Book Rating : 4.4/5 (666 download)

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Book Synopsis Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance by : Vasant, Pandian M.

Download or read book Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance written by Vasant, Pandian M. and published by IGI Global. This book was released on 2012-09-30 with total page 735 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Advancements in Applied Metaheuristic Computing

Author : Dey, Nilanjan
Publisher : IGI Global
ISBN 13 : 1522541527
Total Pages : 335 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Advancements in Applied Metaheuristic Computing by : Dey, Nilanjan

Download or read book Advancements in Applied Metaheuristic Computing written by Dey, Nilanjan and published by IGI Global. This book was released on 2017-11-30 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: Metaheuristic algorithms are present in various applications for different domains. Recently, researchers have conducted studies on the effectiveness of these algorithms in providing optimal solutions to complicated problems. Advancements in Applied Metaheuristic Computing is a crucial reference source for the latest empirical research on methods and approaches that include metaheuristics for further system improvements, and it offers outcomes of employing optimization algorithms. Featuring coverage on a broad range of topics such as manufacturing, genetic programming, and medical imaging, this publication is ideal for researchers, academicians, advanced-level students, and technology developers seeking current research on the use of optimization algorithms in several applications.

Trends in Developing Metaheuristics, Algorithms, and Optimization Approaches

Author : Yin, Peng-Yeng
Publisher : IGI Global
ISBN 13 : 146662146X
Total Pages : 375 pages
Book Rating : 4.4/5 (666 download)

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Book Synopsis Trends in Developing Metaheuristics, Algorithms, and Optimization Approaches by : Yin, Peng-Yeng

Download or read book Trends in Developing Metaheuristics, Algorithms, and Optimization Approaches written by Yin, Peng-Yeng and published by IGI Global. This book was released on 2012-10-31 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: Developments in metaheuristics continue to advance computation beyond its traditional methods. With groundwork built on multidisciplinary research findings; metaheuristics, algorithms, and optimization approaches uses memory manipulations in order to take full advantage of strategic level problem solving. Trends in Developing Metaheuristics, Algorithms, and Optimization Approaches provides insight on the latest advances and analysis of technologies in metaheuristics computing. Offering widespread coverage on topics such as genetic algorithms, differential evolution, and ant colony optimization, this book aims to be a forum researchers, practitioners, and students who wish to learn and apply metaheuristic computing.

Advances in Metaheuristics

Author : Luca Di Gaspero
Publisher : Springer Science & Business Media
ISBN 13 : 146146322X
Total Pages : 193 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Advances in Metaheuristics by : Luca Di Gaspero

Download or read book Advances in Metaheuristics written by Luca Di Gaspero and published by Springer Science & Business Media. This book was released on 2013-03-01 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: Metaheuristics have been a very active research topic for more than two decades. During this time many new metaheuristic strategies have been devised, they have been experimentally tested and improved on challenging benchmark problems, and they have proven to be important tools for tackling optimization tasks in a large number of practical applications. In other words, metaheuristics are nowadays established as one of the main search paradigms for tackling computationally hard problems. Still, there are a large number of research challenges in the area of metaheuristics. These challenges range from more fundamental questions on theoretical properties and performance guarantees, empirical algorithm analysis, the effective configuration of metaheuristic algorithms, approaches to combine metaheuristics with other algorithmic techniques, towards extending the available techniques to tackle ever more challenging problems. This edited volume grew out of the contributions presented at the ninth Metaheuristics International Conference that was held in Udine, Italy, 25-28 July 2011. The conference comprised 117 presentations of peer-reviewed contributions and 3 invited talks, and it has been attended by 169 delegates. The chapters that are collected in this book exemplify contributions to several of the research directions outlined above.

Hybrid Genetic Optimization for IC Chips Thermal Control

Author : Mathew V. K.
Publisher : CRC Press
ISBN 13 : 1000590437
Total Pages : 162 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Hybrid Genetic Optimization for IC Chips Thermal Control by : Mathew V. K.

Download or read book Hybrid Genetic Optimization for IC Chips Thermal Control written by Mathew V. K. and published by CRC Press. This book was released on 2022-06-07 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: The continuous miniaturization of integrated circuit (IC) chips and the increase in the sleekness of the design of electronic components have led to the monumental rise of volumetric heat generation in electronic components. Hybrid Genetic Optimization for IC Chips Thermal Control: With MATLAB® Applications focuses on the detailed optimization strategy carried out to enhance the performance (temperature control) of the IC chips oriented at different positions on a switch-mode power supply (SMPS) board and cooled using air under various heat transfer modes. Seven asymmetric protruding IC chips mounted at different positions on an SMPS board are considered in the present study that is supplied with non-uniform heat fluxes. Key Features: Provides guidance on performance enhancement and reliability of IC chips Provides a detailed hybrid optimization strategy for the optimal arrangement of IC chips on a board The MATLAB program for the hybrid optimization strategy along with its stability analysis is carried out in a detailed manner Enables thermal design engineers to identify the positioning of IC chips on the board to increase their reliability and working cycle

Metaheuristics

Author : Karl F. Doerner
Publisher : Springer Science & Business Media
ISBN 13 : 0387719210
Total Pages : 409 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis Metaheuristics by : Karl F. Doerner

Download or read book Metaheuristics written by Karl F. Doerner and published by Springer Science & Business Media. This book was released on 2007-08-13 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book’s aim is to provide several different kinds of information: a delineation of general metaheuristics methods, a number of state-of-the-art articles from a variety of well-known classical application areas as well as an outlook to modern computational methods in promising new areas. Therefore, this book may equally serve as a textbook in graduate courses for students, as a reference book for people interested in engineering or social sciences, and as a collection of new and promising avenues for researchers working in this field.

Modeling, Analysis, and Applications in Metaheuristic Computing

Author : Peng-Yeng Yin
Publisher :
ISBN 13 : 9781466602700
Total Pages : 0 pages
Book Rating : 4.6/5 (27 download)

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

Download or read book Modeling, Analysis, and Applications in Metaheuristic Computing written by Peng-Yeng Yin and published by . This book was released on 2012 with total page 0 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.

Recent Developments in Metaheuristics

Author : Lionel Amodeo
Publisher : Springer
ISBN 13 : 3319582534
Total Pages : 496 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Recent Developments in Metaheuristics by : Lionel Amodeo

Download or read book Recent Developments in Metaheuristics written by Lionel Amodeo and published by Springer. This book was released on 2017-09-18 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights state-of-the-art developments in metaheuristics research. It examines all aspects of metaheuristic research including new algorithmic developments, applications, new research challenges, theoretical developments, implementation issues, in-depth experimental studies. The book is divided into two sections. Part I is focused on new optimization and modeling techniques based on metaheuristics. The chapters in this section cover topics from multi-objective problems with fuzzy data with triangular-valued objective functions, to hyper-heuristics optimization methodology, designing genetic algorithms, and also the cuckoo search algorithm. The techniques described help to enhance the usability and increase the potential of metaheuristic algorithms. Part II showcases advanced metaheuristic approaches to solve real-life applications issues. This includes an examination of scheduling, the vehicle routing problem, multimedia sensor network, supplier selection, bin packing, objects tracking, and radio frequency identification. In the fields covered in the chapters are of high-impact applications of metaheuristics. The chapters offer innovative applications of metaheuristics that have a potential of widening research frontiers. Altogether, this book offers a comprehensive look at how researchers are currently using metaheuristics in different domains of design and application.

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

Author : Yin, Peng-Yeng
Publisher : IGI Global
ISBN 13 : 1466602716
Total Pages : 446 pages
Book Rating : 4.4/5 (666 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.

Nature-Inspired Methods for Metaheuristics Optimization

Author : Fouad Bennis
Publisher : Springer Nature
ISBN 13 : 3030264580
Total Pages : 503 pages
Book Rating : 4.0/5 (32 download)

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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.

Constraint Handling in Cohort Intelligence Algorithm

Author : Ishaan R. Kale
Publisher : CRC Press
ISBN 13 : 100052048X
Total Pages : 206 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Constraint Handling in Cohort Intelligence Algorithm by : Ishaan R. Kale

Download or read book Constraint Handling in Cohort Intelligence Algorithm written by Ishaan R. Kale and published by CRC Press. This book was released on 2021-12-27 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mechanical Engineering domain problems are generally complex, consisting of different design variables and constraints. These problems may not be solved using gradient-based optimization techniques. The stochastic nature-inspired optimization techniques have been proposed in this book to efficiently handle the complex problems. The nature-inspired algorithms are classified as bio-inspired, swarm, and physics/chemical-based algorithms. Socio-inspired is one of the subdomains of bio-inspired algorithms, and Cohort Intelligence (CI) models the social tendencies of learning candidates with an inherent goal to achieve the best possible position. In this book, CI is investigated by solving ten discrete variable truss structural problems, eleven mixed variable design engineering problems, seventeen linear and nonlinear constrained test problems and two real-world applications from manufacturing domain. Static Penalty Function (SPF) is also adopted to handle the linear and nonlinear constraints, and limitations in CI and SPF approaches are examined. Constraint Handling in Cohort Intelligence Algorithm is a valuable reference to practitioners working in the industry as well as to students and researchers in the area of optimization methods.

Handbook of Metaheuristic Algorithms

Author : Chun-Wei Tsai
Publisher : Elsevier
ISBN 13 : 0443191093
Total Pages : 624 pages
Book Rating : 4.4/5 (431 download)

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Book Synopsis Handbook of Metaheuristic Algorithms by : Chun-Wei Tsai

Download or read book Handbook of Metaheuristic Algorithms written by Chun-Wei Tsai and published by Elsevier. This book was released on 2023-05-30 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Metaheuristic Algorithms: From Fundamental Theories to Advanced Applications provides a brief introduction to metaheuristic algorithms from the ground up, including basic ideas and advanced solutions. Although readers may be able to find source code for some metaheuristic algorithms on the Internet, the coding styles and explanations are generally quite different, and thus requiring expanded knowledge between theory and implementation. This book can also help students and researchers construct an integrated perspective of metaheuristic and unsupervised algorithms for artificial intelligence research in computer science and applied engineering domains. Metaheuristic algorithms can be considered the epitome of unsupervised learning algorithms for the optimization of engineering and artificial intelligence problems, including simulated annealing (SA), tabu search (TS), genetic algorithm (GA), ant colony optimization (ACO), particle swarm optimization (PSO), differential evolution (DE), and others. Distinct from most supervised learning algorithms that need labeled data to learn and construct determination models, metaheuristic algorithms inherit characteristics of unsupervised learning algorithms used for solving complex engineering optimization problems without labeled data, just like self-learning, to find solutions to complex problems. Presents a unified framework for metaheuristics and describes well-known algorithms and their variants Introduces fundamentals and advanced topics for solving engineering optimization problems, e.g., scheduling problems, sensors deployment problems, and clustering problems Includes source code based on the unified framework for metaheuristics used as examples to show how TS, SA, GA, ACO, PSO, DE, parallel metaheuristic algorithm, hybrid metaheuristic, local search, and other advanced technologies are realized in programming languages such as C++ and Python