Metaheuristic Algorithms in Industry 4.0

Metaheuristic Algorithms in Industry 4.0

Author: Pritesh Shah

Publisher: CRC Press

Published: 2021-09-28

Total Pages: 301

ISBN-13: 1000435946

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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.


Metaheuristic Algorithms in Industry 4.0

Metaheuristic Algorithms in Industry 4.0

Author: Pritesh Shah

Publisher: CRC Press

Published: 2021-09-29

Total Pages: 302

ISBN-13: 1000435989

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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.


Metaheuristics for Scheduling in Industrial and Manufacturing Applications

Metaheuristics for Scheduling in Industrial and Manufacturing Applications

Author: Fatos Xhafa

Publisher: Springer Science & Business Media

Published: 2008-06-21

Total Pages: 362

ISBN-13: 3540789847

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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

Metaheuristics

Author: Karl F. Doerner

Publisher: Springer Science & Business Media

Published: 2007-08-13

Total Pages: 409

ISBN-13: 0387719210

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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.


Metaheuristic Optimization via Memory and Evolution

Metaheuristic Optimization via Memory and Evolution

Author: Cesar Rego

Publisher: Springer Science & Business Media

Published: 2006-03-30

Total Pages: 472

ISBN-13: 0387236678

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Tabu Search (TS) and, more recently, Scatter Search (SS) have proved highly effective in solving a wide range of optimization problems, and have had a variety of applications in industry, science, and government. The goal of Metaheuristic Optimization via Memory and Evolution: Tabu Search and Scatter Search is to report original research on algorithms and applications of tabu search, scatter search or both, as well as variations and extensions having "adaptive memory programming" as a primary focus. Individual chapters identify useful new implementations or new ways to integrate and apply the principles of TS and SS, or that prove new theoretical results, or describe the successful application of these methods to real world problems.


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

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

Author: Vasant, Pandian M.

Publisher: IGI Global

Published: 2012-09-30

Total Pages: 735

ISBN-13: 1466620870

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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.


Computational Intelligence Systems in Industrial Engineering

Computational Intelligence Systems in Industrial Engineering

Author: Cengiz Kahraman

Publisher: Springer Science & Business Media

Published: 2012-11-05

Total Pages: 683

ISBN-13: 9491216775

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Industrial engineering is a branch of engineering dealing with the optimization of complex processes or systems. It is concerned with the development, improvement, implementation and evaluation of production and service systems. Computational Intelligence Systems find a wide application area in industrial engineering: neural networks in forecasting, fuzzy sets in capital budgeting, ant colony optimization in scheduling, Simulated Annealing in optimization, etc. This book will include most of the application areas of industrial engineering through these computational intelligence systems. In the literature, there is no book including many real and practical applications of Computational Intelligence Systems from the point of view of Industrial Engineering. Every chapter will include explanatory and didactic applications. It is aimed that the book will be a main source for MSc and PhD students.


Robotics and Automation in Industry 4.0

Robotics and Automation in Industry 4.0

Author: Nidhi Sindhwani

Publisher: CRC Press

Published: 2024-02-09

Total Pages: 453

ISBN-13: 1003837352

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The book presents the innovative aspects of smart industries and intelligent technologies involving Robotics and Automation. It discusses the challenges in the design of autonomous robots and provides an understanding of how different systems ommunicate with each other, allowing cooperation with other human systems and operators in real time. Robotics and Automation in Industry 4.0: Smart Industries and Intelligent Technologies offers research articles, flow charts, algorithms, and examples based on daily life in automation and robotics related to the building of Industry 4.0. It presents disruptive technology applications related to Smart Industries and talks about how robotics is an important Industry 4.0 technology that offers a wide range of capabilities and has improved automation systems by doing repetitive tasks with more accuracy and at a lower cost. The book discusses how frontline healthcare staff can evaluate, monitor, and treat patients from a safe distance by using robotic and telerobotic systems to minimize the risk of infectious disease transmission. Artificial intelligence (AI) and machine learning (ML) are looked at and the book offers a comprehensive overview of the key challenges surrounding the Internet of Things (IoT) and AI synergy, including current and future applications with significant societal value. An ideal read for scientists, research scholars, entrepreneurs, industrialists, academicians, and various other professionals who are interested in exploring innovations in the applicational areas of AI, IoT, and ML related to Robotics and Automation.


Author:

Publisher: Springer Nature

Published:

Total Pages: 415

ISBN-13: 9464634960

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