Meta Heuristics

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Essentials of Metaheuristics (Second Edition)

Author : Sean Luke
Publisher :
ISBN 13 : 9781300549628
Total Pages : 242 pages
Book Rating : 4.5/5 (496 download)

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Book Synopsis Essentials of Metaheuristics (Second Edition) by : Sean Luke

Download or read book Essentials of Metaheuristics (Second Edition) written by Sean Luke and published by . This book was released on 2012-12-20 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

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.

Meta-Heuristics

Author : Ibrahim H. Osman
Publisher : Springer Science & Business Media
ISBN 13 : 1461313619
Total Pages : 676 pages
Book Rating : 4.4/5 (613 download)

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Book Synopsis Meta-Heuristics by : Ibrahim H. Osman

Download or read book Meta-Heuristics written by Ibrahim H. Osman and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 676 pages. Available in PDF, EPUB and Kindle. Book excerpt: Meta-heuristics have developed dramatically since their inception in the early 1980s. They have had widespread success in attacking a variety of practical and difficult combinatorial optimization problems. These families of approaches include, but are not limited to greedy random adaptive search procedures, genetic algorithms, problem-space search, neural networks, simulated annealing, tabu search, threshold algorithms, and their hybrids. They incorporate concepts based on biological evolution, intelligent problem solving, mathematical and physical sciences, nervous systems, and statistical mechanics. Since the 1980s, a great deal of effort has been invested in the field of combinatorial optimization theory in which heuristic algorithms have become an important area of research and applications. This volume is drawn from the first conference on Meta-Heuristics and contains 41 papers on the state-of-the-art in heuristic theory and applications. The book treats the following meta-heuristics and applications: Genetic Algorithms, Simulated Annealing, Tabu Search, Networks & Graphs, Scheduling and Control, TSP, and Vehicle Routing Problems. It represents research from the fields of Operations Research, Management Science, Artificial Intelligence and Computer Science.

Handbook of Metaheuristics

Author : Michel Gendreau
Publisher : Springer
ISBN 13 : 3319910868
Total Pages : 611 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Handbook of Metaheuristics by : Michel Gendreau

Download or read book Handbook of Metaheuristics written by Michel Gendreau and published by Springer. This book was released on 2018-09-20 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: The third edition of this handbook is designed to provide a broad coverage of the concepts, implementations, and applications in metaheuristics. The book’s chapters serve as stand-alone presentations giving both the necessary underpinnings as well as practical guides for implementation. The nature of metaheuristics invites an analyst to modify basic methods in response to problem characteristics, past experiences, and personal preferences, and the chapters in this handbook are designed to facilitate this process as well. This new edition has been fully revised and features new chapters on swarm intelligence and automated design of metaheuristics from flexible algorithm frameworks. The authors who have contributed to this volume represent leading figures from the metaheuristic community and are responsible for pioneering contributions to the fields they write about. Their collective work has significantly enriched the field of optimization in general and combinatorial optimization in particular.Metaheuristics are solution methods that orchestrate an interaction between local improvement procedures and higher level strategies to create a process capable of escaping from local optima and performing a robust search of a solution space. In addition, many new and exciting developments and extensions have been observed in the last few years. Hybrids of metaheuristics with other optimization techniques, like branch-and-bound, mathematical programming or constraint programming are also increasingly popular. On the front of applications, metaheuristics are now used to find high-quality solutions to an ever-growing number of complex, ill-defined real-world problems, in particular combinatorial ones. This handbook should continue to be a great reference for researchers, graduate students, as well as practitioners interested in metaheuristics.

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.

Metaheuristics

Author : El-Ghazali Talbi
Publisher : John Wiley & Sons
ISBN 13 : 0470496908
Total Pages : 625 pages
Book Rating : 4.4/5 (74 download)

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Book Synopsis Metaheuristics by : El-Ghazali Talbi

Download or read book Metaheuristics written by El-Ghazali Talbi and published by John Wiley & Sons. This book was released on 2009-05-27 with total page 625 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unified view of metaheuristics This book provides a complete background on metaheuristics and shows readers how to design and implement efficient algorithms to solve complex optimization problems across a diverse range of applications, from networking and bioinformatics to engineering design, routing, and scheduling. It presents the main design questions for all families of metaheuristics and clearly illustrates how to implement the algorithms under a software framework to reuse both the design and code. Throughout the book, the key search components of metaheuristics are considered as a toolbox for: Designing efficient metaheuristics (e.g. local search, tabu search, simulated annealing, evolutionary algorithms, particle swarm optimization, scatter search, ant colonies, bee colonies, artificial immune systems) for optimization problems Designing efficient metaheuristics for multi-objective optimization problems Designing hybrid, parallel, and distributed metaheuristics Implementing metaheuristics on sequential and parallel machines Using many case studies and treating design and implementation independently, this book gives readers the skills necessary to solve large-scale optimization problems quickly and efficiently. It is a valuable reference for practicing engineers and researchers from diverse areas dealing with optimization or machine learning; and graduate students in computer science, operations research, control, engineering, business and management, and applied mathematics.

Search and Optimization by Metaheuristics

Author : Ke-Lin Du
Publisher : Birkhäuser
ISBN 13 : 3319411926
Total Pages : 434 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Search and Optimization by Metaheuristics by : Ke-Lin Du

Download or read book Search and Optimization by Metaheuristics written by Ke-Lin Du and published by Birkhäuser. This book was released on 2016-07-20 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a comprehensive introduction to nature-inspired metaheuristic methods for search and optimization, including the latest trends in evolutionary algorithms and other forms of natural computing. Over 100 different types of these methods are discussed in detail. The authors emphasize non-standard optimization problems and utilize a natural approach to the topic, moving from basic notions to more complex ones. An introductory chapter covers the necessary biological and mathematical backgrounds for understanding the main material. Subsequent chapters then explore almost all of the major metaheuristics for search and optimization created based on natural phenomena, including simulated annealing, recurrent neural networks, genetic algorithms and genetic programming, differential evolution, memetic algorithms, particle swarm optimization, artificial immune systems, ant colony optimization, tabu search and scatter search, bee and bacteria foraging algorithms, harmony search, biomolecular computing, quantum computing, and many others. General topics on dynamic, multimodal, constrained, and multiobjective optimizations are also described. Each chapter includes detailed flowcharts that illustrate specific algorithms and exercises that reinforce important topics. Introduced in the appendix are some benchmarks for the evaluation of metaheuristics. Search and Optimization by Metaheuristics is intended primarily as a textbook for graduate and advanced undergraduate students specializing in engineering and computer science. It will also serve as a valuable resource for scientists and researchers working in these areas, as well as those who are interested in search and optimization methods.

Meta-heuristic and Evolutionary Algorithms for Engineering Optimization

Author : Omid Bozorg-Haddad
Publisher : John Wiley & Sons
ISBN 13 : 1119386993
Total Pages : 306 pages
Book Rating : 4.1/5 (193 download)

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Book Synopsis Meta-heuristic and Evolutionary Algorithms for Engineering Optimization by : Omid Bozorg-Haddad

Download or read book Meta-heuristic and Evolutionary Algorithms for Engineering Optimization written by Omid Bozorg-Haddad and published by John Wiley & Sons. This book was released on 2017-10-09 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: A detailed review of a wide range of meta-heuristic and evolutionary algorithms in a systematic manner and how they relate to engineering optimization problems This book introduces the main metaheuristic algorithms and their applications in optimization. It describes 20 leading meta-heuristic and evolutionary algorithms and presents discussions and assessments of their performance in solving optimization problems from several fields of engineering. The book features clear and concise principles and presents detailed descriptions of leading methods such as the pattern search (PS) algorithm, the genetic algorithm (GA), the simulated annealing (SA) algorithm, the Tabu search (TS) algorithm, the ant colony optimization (ACO), and the particle swarm optimization (PSO) technique. Chapter 1 of Meta-heuristic and Evolutionary Algorithms for Engineering Optimization provides an overview of optimization and defines it by presenting examples of optimization problems in different engineering domains. Chapter 2 presents an introduction to meta-heuristic and evolutionary algorithms and links them to engineering problems. Chapters 3 to 22 are each devoted to a separate algorithm— and they each start with a brief literature review of the development of the algorithm, and its applications to engineering problems. The principles, steps, and execution of the algorithms are described in detail, and a pseudo code of the algorithm is presented, which serves as a guideline for coding the algorithm to solve specific applications. This book: Introduces state-of-the-art metaheuristic algorithms and their applications to engineering optimization; Fills a gap in the current literature by compiling and explaining the various meta-heuristic and evolutionary algorithms in a clear and systematic manner; Provides a step-by-step presentation of each algorithm and guidelines for practical implementation and coding of algorithms; Discusses and assesses the performance of metaheuristic algorithms in multiple problems from many fields of engineering; Relates optimization algorithms to engineering problems employing a unifying approach. Meta-heuristic and Evolutionary Algorithms for Engineering Optimization is a reference intended for students, engineers, researchers, and instructors in the fields of industrial engineering, operations research, optimization/mathematics, engineering optimization, and computer science. OMID BOZORG-HADDAD, PhD, is Professor in the Department of Irrigation and Reclamation Engineering at the University of Tehran, Iran. MOHAMMAD SOLGI, M.Sc., is Teacher Assistant for M.Sc. courses at the University of Tehran, Iran. HUGO A. LOÁICIGA, PhD, is Professor in the Department of Geography at the University of California, Santa Barbara, United States of America.

An Introduction to Metaheuristics for Optimization

Author : Bastien Chopard
Publisher : Springer
ISBN 13 : 3319930737
Total Pages : 226 pages
Book Rating : 4.3/5 (199 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.

Heuristics, Metaheuristics and Approximate Methods in Planning and Scheduling

Author : Ghaith Rabadi
Publisher : Springer
ISBN 13 : 3319260243
Total Pages : 264 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Heuristics, Metaheuristics and Approximate Methods in Planning and Scheduling by : Ghaith Rabadi

Download or read book Heuristics, Metaheuristics and Approximate Methods in Planning and Scheduling written by Ghaith Rabadi and published by Springer. This book was released on 2016-01-27 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: The scope of this book is limited to heuristics, metaheuristics, and approximate methods and algorithms as applied to planning and scheduling problems. While it is not possible to give a comprehensive treatment of this topic in one book, the aim of this work is to provide the reader with a diverse set of planning and scheduling problems and different heuristic approaches to solve them. The problems range from traditional single stage and parallel machine problems to more modern settings such as robotic cells and flexible job shop networks. Furthermore, some chapters deal with deterministic problems while some others treat stochastic versions of the problems. Unlike most of the literature that deals with planning and scheduling problems in the manufacturing and production environments, in this book the environments were extended to nontraditional applications such as spatial scheduling (optimizing space over time), runway scheduling, and surgical scheduling. The solution methods used in the different chapters of the book also spread from well-established heuristics and metaheuristics such as Genetic Algorithms and Ant Colony Optimization to more recent ones such as Meta-RaPS.

Metaheuristics

Author : Mauricio G.C. Resende
Publisher : Springer Science & Business Media
ISBN 13 : 9781402076534
Total Pages : 744 pages
Book Rating : 4.0/5 (765 download)

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Book Synopsis Metaheuristics by : Mauricio G.C. Resende

Download or read book Metaheuristics written by Mauricio G.C. Resende and published by Springer Science & Business Media. This book was released on 2003-11-30 with total page 744 pages. Available in PDF, EPUB and Kindle. Book excerpt: Combinatorial optimization is the process of finding the best, or optimal, so lution for problems with a discrete set of feasible solutions. Applications arise in numerous settings involving operations management and logistics, such as routing, scheduling, packing, inventory and production management, lo cation, logic, and assignment of resources. The economic impact of combi natorial optimization is profound, affecting sectors as diverse as transporta tion (airlines, trucking, rail, and shipping), forestry, manufacturing, logistics, aerospace, energy (electrical power, petroleum, and natural gas), telecommu nications, biotechnology, financial services, and agriculture. While much progress has been made in finding exact (provably optimal) so lutions to some combinatorial optimization problems, using techniques such as dynamic programming, cutting planes, and branch and cut methods, many hard combinatorial problems are still not solved exactly and require good heuristic methods. Moreover, reaching "optimal solutions" is in many cases meaningless, as in practice we are often dealing with models that are rough simplifications of reality. The aim of heuristic methods for combinatorial op timization is to quickly produce good-quality solutions, without necessarily providing any guarantee of solution quality. Metaheuristics are high level procedures that coordinate simple heuristics, such as local search, to find solu tions that are of better quality than those found by the simple heuristics alone: Modem metaheuristics include simulated annealing, genetic algorithms, tabu search, GRASP, scatter search, ant colony optimization, variable neighborhood search, and their hybrids.

Essays and Surveys in Metaheuristics

Author : Celso C. Ribeiro
Publisher : Springer Science & Business Media
ISBN 13 : 1461515076
Total Pages : 647 pages
Book Rating : 4.4/5 (615 download)

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Book Synopsis Essays and Surveys in Metaheuristics by : Celso C. Ribeiro

Download or read book Essays and Surveys in Metaheuristics written by Celso C. Ribeiro and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 647 pages. Available in PDF, EPUB and Kindle. Book excerpt: Finding exact solutions to many combinatorial optimization problems in busi ness, engineering, and science still poses a real challenge, despite the impact of recent advances in mathematical programming and computer technology. New fields of applications, such as computational biology, electronic commerce, and supply chain management, bring new challenges and needs for algorithms and optimization techniques. Metaheuristics are master procedures that guide and modify the operations of subordinate heuristics, to produce improved approx imate solutions to hard optimization problems with respect to more simple algorithms. They also provide fast and robust tools, producing high-quality solutions in reasonable computation times. The field of metaheuristics has been fast evolving in recent years. Tech niques such as simulated annealing, tabu search, genetic algorithms, scatter search, greedy randomized adaptive search, variable neighborhood search, ant systems, and their hybrids are currently among the most efficient and robust optimization strategies to find high-quality solutions to many real-life optimiza tion problems. A very large nmnber of successful applications of metaheuristics are reported in the literature and spread throughout many books, journals, and conference proceedings. A series of international conferences entirely devoted to the theory, applications, and computational developments in metaheuristics has been attracting an increasing number of participants, from universities and the industry.

Metaheuristics in Machine Learning: Theory and Applications

Author : Diego Oliva
Publisher : Springer Nature
ISBN 13 : 3030705420
Total Pages : 765 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Metaheuristics in Machine Learning: Theory and Applications by : Diego Oliva

Download or read book Metaheuristics in Machine Learning: Theory and Applications written by Diego Oliva and published by Springer Nature. This book was released on with total page 765 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Metaheuristics and Optimization in Computer and Electrical Engineering

Author : Navid Razmjooy
Publisher : Springer Nature
ISBN 13 : 3030566897
Total Pages : 311 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Metaheuristics and Optimization in Computer and Electrical Engineering by : Navid Razmjooy

Download or read book Metaheuristics and Optimization in Computer and Electrical Engineering written by Navid Razmjooy and published by Springer Nature. This book was released on 2020-11-16 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of artificial intelligence, especially in the field of optimization is increasing day by day. The purpose of this book is to explore the possibility of using different kinds of optimization algorithms to advance and enhance the tools used for computer and electrical engineering purposes.

Metaheuristics for Scheduling in Industrial and Manufacturing Applications

Author : Fatos Xhafa
Publisher : Springer Science & Business Media
ISBN 13 : 3540789847
Total Pages : 362 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Metaheuristics for Scheduling in Industrial and Manufacturing Applications by : Fatos Xhafa

Download or read book Metaheuristics for Scheduling in Industrial and Manufacturing Applications written by Fatos Xhafa and published by Springer Science & Business Media. This book was released on 2008-06-21 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the past decades scheduling has been among the most studied op- mization problemsanditisstillanactiveareaofresearch!Schedulingappears in many areas of science, engineering and industry and takes di?erent forms depending on the restrictions and optimization criteria of the operating en- ronments [8]. For instance, in optimization and computer science, scheduling has been de?ned as “the allocation of tasks to resources over time in order to achieve optimality in one or more objective criteria in an e?cient way” and in production as “production schedule, i. e. , the planning of the production or the sequence of operations according to which jobs pass through machines and is optimal with respect to certain optimization criteria. ” Although there is a standardized form of stating any scheduling problem, namely “e?cient allocation ofn jobs onm machines –which can process no more than one activity at a time– with the objective to optimize some - jective function of the job completion times”, scheduling is in fact a family of problems. Indeed, several parameters intervene in the problem de?nition: (a) job characteristics (preemptive or not, precedence constraints, release dates, etc. ); (b) resource environment (single vs. parallel machines, un- lated machines, identical or uniform machines, etc. ); (c) optimization criteria (minimize total tardiness, the number of late jobs, makespan, ?owtime, etc. ; maximize resource utilization, etc. ); and, (d) scheduling environment (static vs. dynamic,intheformerthenumberofjobstobeconsideredandtheirready times are available while in the later the number of jobs and their charact- istics change over time).

Metaheuristics for Hard Optimization

Author : Johann Dréo
Publisher : Springer Science & Business Media
ISBN 13 : 3540309667
Total Pages : 372 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Metaheuristics for Hard Optimization by : Johann Dréo

Download or read book Metaheuristics for Hard Optimization written by Johann Dréo and published by Springer Science & Business Media. This book was released on 2006-01-16 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contains case studies from engineering and operations research Includes commented literature for each chapter

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.