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Risk Controlled Simultaneous Scheduling Of Machines And Agvs Using A Quantile Based Optimization Approach
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Book Synopsis Risk-Controlled Simultaneous Scheduling of Machines and AGVs Using a Quantile-based Optimization Approach by : Wei-Lun Hu
Download or read book Risk-Controlled Simultaneous Scheduling of Machines and AGVs Using a Quantile-based Optimization Approach written by Wei-Lun Hu and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Optimization of Simultaneous Scheduling for Machines and Automated Guided Vehicles Using Fuzzy Genetic Algorithm by : Mostafa Badakhshian
Download or read book Optimization of Simultaneous Scheduling for Machines and Automated Guided Vehicles Using Fuzzy Genetic Algorithm written by Mostafa Badakhshian and published by . This book was released on 2009 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: Flexible manufacturing system (FMS) has been introduced by the researchers as an integrated manufacturing environment. Automated guided vehicles (AGVs) introduced as the main tool of material handling systems in FMS. While the scheduling of AGVs and machines are highly related; simultaneous scheduling of machines and AGVs has been proposed in the literature. Genetic algorithm (GA) proposed as a robust tool for optimization of scheduling problems. Setting the proper crossover and mutation rates are of vital importance for the performance of the GA. Fuzzy logic controllers (FLCs) have been used in the literature to control key parameters of the GA which is addressed as fuzzy GA (FGA). A new application of FGA method in simultaneous scheduling of AGVs and machines is presented. The general GA is modified for the aforementioned application; more over an FLC is developed to control mutation and crossover rates of the GA. The objective of proposed FGA method is to minimize the makespan, production completion time of all jobs that they are produced simultaneously. An optimal sequence of operations is obtained by GA. There is a heuristic algorithm to assign the AGVs to the operations. As the main findings, the performance of GA in simultaneous scheduling of AGVs and machines is enhanced by using proposed method, furthermore a new mutation operator has been proposed. Several experiments have been done to the proposed test cases. The results showed that tournament selection scheme may outperform roulette wheel in this problem. Various combinations of population size and number of generations are compared to each other in terms of their objective function. In large scale problems FGA method may outperforms GA method, while in small and medium problems they have the same performance. The fluctuation of obtained makespan in FGA method is less than GA method which means that it is more probable to find a better solution by FGA rather than GA.
Book Synopsis Digital-Twin-Based Simultaneous Scheduling of Machines and Multiple-Load AGVs by :
Download or read book Digital-Twin-Based Simultaneous Scheduling of Machines and Multiple-Load AGVs written by and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Dynamic Scheduling and Sequencing of Machines and Automated Guided Vehicles Using Genetic Algorithms by : Amirabbas Tabatabaei
Download or read book Dynamic Scheduling and Sequencing of Machines and Automated Guided Vehicles Using Genetic Algorithms written by Amirabbas Tabatabaei and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scheduling of machines has been interested in flexible manufacturing systems due to the flexibility and simultaneous task process capability of such production systems. Advanced material handling systems such as automated guided vehicles are being used in flexible manufacturing systems. Automated guided vehicles are flexible and easy to utilize in flexible manufacturing systems. Therefore, dynamic simultaneous scheduling and sequencing of flexible manufacturing systems and automated guided vehicles, are considered as the main focus of this study. Scheduling of machines and automated guided vehicles, if considered separately, are NP-Hard problems. Similarly, simultaneous scheduling of machines and automated vehicles are NP-Hard. Although there are some studies on static scheduling of machines and vehicles, dynamic scheduling has not been studied thoroughly in the literature. Population based search algorithms have been used to solve complex problems and in order to find solution sets. In this study, a genetic algorithm is designed to propose solutions for simultaneous scheduling and sequencing of machines and automated guided vehicles in flexible manufacturing systems environments in dynamic situation. In order to assist designers of manufacturing systems, two design variables were added to mathematical model presented in this study. These two design variables were battery charge capacity and number of active automated guided vehicles in the system. A specific time frame was assumed for each job set to schedule machines and automated guided vehicles dynamically. The genetic algorithm was initially validated by bench mark problems from previous studies. Ten job sets previously scheduled by other researchers using heuristic ii and meta heuristic approaches were used. Precedence constrain connects tasks by a network. There are 4 layouts which define machine locations and automated guided vehicle paths. Through solving the static scheduling problem of previous studies, the genetic algorithm was validated. Thereafter, a set of dynamic scheduling problem was developed from previous bench mark problems and solved using the modified model proposed and validated in this study. Dynamic scheduling problem results show that the genetic algorithm is not limited by the number of components to schedule in the mathematical model. In addition, it was found that as the number of active automated guided vehicles increase in the system, the total completion time decreases. This fact is due to the availability of automated guided vehicle to travel demand. Although having more vehicles in the system may increase the costs of production, one could argue the advantages and disadvantages. According to the results, the total completion time for the first static and dynamic scheduling problems (Job set 1, Layout 1) for one to four vehicles are 161 to 76 and 481 to 186 respectively. Another observation was finding best vehicle type based on the battery charge capacity. Automated guided vehicles maintenance and costs are related to the type and their ability to run with a single charge. Therefore, it is important to choose vehicles which fulfill the needs and requirements of the system. The battery charge capacities were from 25 to 100 which affects the total completion times for static and dynamic scheduling problems relatively. The total completion times for static scheduling problems are 100 to 96 for battery capacities 25 to 100. Likewise dynamic scheduling problem completion times are 291.5 to 272.5.
Book Synopsis 2020 Winter Simulation Conference (WSC) by : IEEE Staff
Download or read book 2020 Winter Simulation Conference (WSC) written by IEEE Staff and published by . This book was released on 2020-12-14 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: WSC is the premier international forum for disseminating recent advances in the field of system simulation In addition to a technical program of unsurpassed scope and quality, WSC provides the central meeting for practitioners, researchers, and vendors
Download or read book Logistics 4.0 written by Turan Paksoy and published by CRC Press. This book was released on 2020-12-17 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: Industrial revolutions have impacted both, manufacturing and service. From the steam engine to digital automated production, the industrial revolutions have conduced significant changes in operations and supply chain management (SCM) processes. Swift changes in manufacturing and service systems have led to phenomenal improvements in productivity. The fast-paced environment brings new challenges and opportunities for the companies that are associated with the adaptation to the new concepts such as Internet of Things (IoT) and Cyber Physical Systems, artificial intelligence (AI), robotics, cyber security, data analytics, block chain and cloud technology. These emerging technologies facilitated and expedited the birth of Logistics 4.0. Industrial Revolution 4.0 initiatives in SCM has attracted stakeholders’ attentions due to it is ability to empower using a set of technologies together that helps to execute more efficient production and distribution systems. This initiative has been called Logistics 4.0 of the fourth Industrial Revolution in SCM due to its high potential. Connecting entities, machines, physical items and enterprise resources to each other by using sensors, devices and the internet along the supply chains are the main attributes of Logistics 4.0. IoT enables customers to make more suitable and valuable decisions due to the data-driven structure of the Industry 4.0 paradigm. Besides that, the system’s ability of gathering and analyzing information about the environment at any given time and adapting itself to the rapid changes add significant value to the SCM processes. In this peer-reviewed book, experts from all over the world, in the field present a conceptual framework for Logistics 4.0 and provide examples for usage of Industry 4.0 tools in SCM. This book is a work that will be beneficial for both practitioners and students and academicians, as it covers the theoretical framework, on the one hand, and includes examples of practice and real world.
Book Synopsis Handbook of Simulation by : Jerry Banks
Download or read book Handbook of Simulation written by Jerry Banks and published by John Wiley & Sons. This book was released on 1998-09-14 with total page 868 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dieses Buch ist eine unschätzbare Informationsquelle für alle Ingenieure, Designer, Manager und Techniker bei Entwicklung, Studium und Anwendung einer großen Vielzahl von Simulationstechniken. Es vereint die Arbeit internationaler Simulationsexperten aus Industrie und Forschung. Alle Aspekte der Simulation werden in diesem umfangreichen Nachschlagewerk abgedeckt. Der Leser wird vertraut gemacht mit den verschiedenen Techniken von Industriesimulationen sowie mit Einsatz, Anwendungen und Entwicklungen. Neueste Fortschritte wie z.B. objektorientierte Programmierung werden ebenso behandelt wie Richtlinien für den erfolgreichen Umgang mit simulationsgestützten Prozessen. Auch gibt es eine Liste mit den wichtigsten Vertriebs- und Zulieferadressen. (10/98)
Book Synopsis Simulation Modeling and Analysis with ARENA by : Tayfur Altiok
Download or read book Simulation Modeling and Analysis with ARENA written by Tayfur Altiok and published by Elsevier. This book was released on 2010-07-26 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simulation Modeling and Analysis with Arena is a highly readable textbook which treats the essentials of the Monte Carlo discrete-event simulation methodology, and does so in the context of a popular Arena simulation environment. It treats simulation modeling as an in-vitro laboratory that facilitates the understanding of complex systems and experimentation with what-if scenarios in order to estimate their performance metrics. The book contains chapters on the simulation modeling methodology and the underpinnings of discrete-event systems, as well as the relevant underlying probability, statistics, stochastic processes, input analysis, model validation and output analysis. All simulation-related concepts are illustrated in numerous Arena examples, encompassing production lines, manufacturing and inventory systems, transportation systems, and computer information systems in networked settings. - Introduces the concept of discrete event Monte Carlo simulation, the most commonly used methodology for modeling and analysis of complex systems - Covers essential workings of the popular animated simulation language, ARENA, including set-up, design parameters, input data, and output analysis, along with a wide variety of sample model applications from production lines to transportation systems - Reviews elements of statistics, probability, and stochastic processes relevant to simulation modeling
Book Synopsis Simulation Modeling and Analysis with Expertfit Software by : Averill Law
Download or read book Simulation Modeling and Analysis with Expertfit Software written by Averill Law and published by McGraw-Hill Science/Engineering/Math. This book was released on 2006-07-21 with total page 792 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the publication of the first edition in 1982, the goal of Simulation Modeling and Analysis has always been to provide a comprehensive, state-of-the-art, and technically correct treatment of all important aspects of a simulation study. The book strives to make this material understandable by the use of intuition and numerous figures, examples, and problems. It is equally well suited for use in university courses, simulation practice, and self study. The book is widely regarded as the “bible” of simulation and now has more than 100,000 copies in print. The book can serve as the primary text for a variety of courses; for example: • A first course in simulation at the junior, senior, or beginning-graduate-student level in engineering, manufacturing, business, or computer science (Chaps. 1 through 4, and parts of Chaps. 5 through 9). At the end of such a course, the students will be prepared to carry out complete and effective simulation studies, and to take advanced simulation courses. • A second course in simulation for graduate students in any of the above disciplines (most of Chaps. 5 through 12). After completing this course, the student should be familiar with the more advanced methodological issues involved in a simulation study, and should be prepared to understand and conduct simulation research. • An introduction to simulation as part of a general course in operations research or management science (part of Chaps. 1, 3, 5, 6, and 9).
Book Synopsis Bayesian Networks by : Olivier Pourret
Download or read book Bayesian Networks written by Olivier Pourret and published by John Wiley & Sons. This book was released on 2008-04-30 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are growing in popularity. Their versatility and modelling power is now employed across a variety of fields for the purposes of analysis, simulation, prediction and diagnosis. This book provides a general introduction to Bayesian networks, defining and illustrating the basic concepts with pedagogical examples and twenty real-life case studies drawn from a range of fields including medicine, computing, natural sciences and engineering. Designed to help analysts, engineers, scientists and professionals taking part in complex decision processes to successfully implement Bayesian networks, this book equips readers with proven methods to generate, calibrate, evaluate and validate Bayesian networks. The book: Provides the tools to overcome common practical challenges such as the treatment of missing input data, interaction with experts and decision makers, determination of the optimal granularity and size of the model. Highlights the strengths of Bayesian networks whilst also presenting a discussion of their limitations. Compares Bayesian networks with other modelling techniques such as neural networks, fuzzy logic and fault trees. Describes, for ease of comparison, the main features of the major Bayesian network software packages: Netica, Hugin, Elvira and Discoverer, from the point of view of the user. Offers a historical perspective on the subject and analyses future directions for research. Written by leading experts with practical experience of applying Bayesian networks in finance, banking, medicine, robotics, civil engineering, geology, geography, genetics, forensic science, ecology, and industry, the book has much to offer both practitioners and researchers involved in statistical analysis or modelling in any of these fields.
Book Synopsis Modeling and Optimization in Manufacturing by : Catalin I. Pruncu
Download or read book Modeling and Optimization in Manufacturing written by Catalin I. Pruncu and published by John Wiley & Sons. This book was released on 2021-07-19 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the state-of-the-art in multiscale modeling and optimization in manufacturing from two leading voices in the field Modeling and Optimization in Manufacturing delivers a comprehensive approach to various manufacturing processes and shows readers how multiscale modeling and optimization processes help improve upon them. The book elaborates on the foundations and applications of computational modeling and optimization processes, as well as recent developments in the field. It offers discussions of manufacturing processes, including forming, machining, casting, joining, coating, and additive manufacturing, and how computer simulations have influenced their development. Examples for each category of manufacturing are provided in the text, and industrial applications are described for the reader. The distinguished authors also provide an insightful perspective on likely future trends and developments in manufacturing modeling and optimization, including the use of large materials databases and machine learning. Readers will also benefit from the inclusion of: A thorough introduction to the origins of manufacturing, the history of traditional and advanced manufacturing, and recent progress in manufacturing An exploration of advanced manufacturing and the environmental impact and significance of manufacturing Practical discussions of the economic importance of advanced manufacturing An examination of the sustainability of advanced manufacturing, and developing and future trends in manufacturing Perfect for materials scientists, mechanical engineers, and process engineers, Modeling and Optimization in Manufacturing will also earn a place in the libraries of engineering scientists in industries seeking a one-stop reference on multiscale modeling and optimization in manufacturing.
Book Synopsis Generalized Linear Models by : Raymond H. Myers
Download or read book Generalized Linear Models written by Raymond H. Myers and published by John Wiley & Sons. This book was released on 2012-01-20 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition "The obvious enthusiasm of Myers, Montgomery, and Vining and their reliance on their many examples as a major focus of their pedagogy make Generalized Linear Models a joy to read. Every statistician working in any area of applied science should buy it and experience the excitement of these new approaches to familiar activities." —Technometrics Generalized Linear Models: With Applications in Engineering and the Sciences, Second Edition continues to provide a clear introduction to the theoretical foundations and key applications of generalized linear models (GLMs). Maintaining the same nontechnical approach as its predecessor, this update has been thoroughly extended to include the latest developments, relevant computational approaches, and modern examples from the fields of engineering and physical sciences. This new edition maintains its accessible approach to the topic by reviewing the various types of problems that support the use of GLMs and providing an overview of the basic, related concepts such as multiple linear regression, nonlinear regression, least squares, and the maximum likelihood estimation procedure. Incorporating the latest developments, new features of this Second Edition include: A new chapter on random effects and designs for GLMs A thoroughly revised chapter on logistic and Poisson regression, now with additional results on goodness of fit testing, nominal and ordinal responses, and overdispersion A new emphasis on GLM design, with added sections on designs for regression models and optimal designs for nonlinear regression models Expanded discussion of weighted least squares, including examples that illustrate how to estimate the weights Illustrations of R code to perform GLM analysis The authors demonstrate the diverse applications of GLMs through numerous examples, from classical applications in the fields of biology and biopharmaceuticals to more modern examples related to engineering and quality assurance. The Second Edition has been designed to demonstrate the growing computational nature of GLMs, as SAS®, Minitab®, JMP®, and R software packages are used throughout the book to demonstrate fitting and analysis of generalized linear models, perform inference, and conduct diagnostic checking. Numerous figures and screen shots illustrating computer output are provided, and a related FTP site houses supplementary material, including computer commands and additional data sets. Generalized Linear Models, Second Edition is an excellent book for courses on regression analysis and regression modeling at the upper-undergraduate and graduate level. It also serves as a valuable reference for engineers, scientists, and statisticians who must understand and apply GLMs in their work.
Book Synopsis Operations Research Proceedings 2019 by : Janis S. Neufeld
Download or read book Operations Research Proceedings 2019 written by Janis S. Neufeld and published by Springer Nature. This book was released on 2020-09-24 with total page 734 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers a selection of peer-reviewed papers presented at the International Conference on Operations Research (OR 2019), which was held at Technische Universität Dresden, Germany, on September 4-6, 2019, and was jointly organized by the German Operations Research Society (GOR) the Austrian Operations Research Society (ÖGOR), and the Swiss Operational Research Society (SOR/ASRO). More than 600 scientists, practitioners and students from mathematics, computer science, business/economics and related fields attended the conference and presented more than 400 papers in plenary presentations, parallel topic streams, as well as special award sessions. The respective papers discuss classical mathematical optimization, statistics and simulation techniques. These are complemented by computer science methods, and by tools for processing data, designing and implementing information systems. The book also examines recent advances in information technology, which allow big data volumes to be processed and enable real-time predictive and prescriptive business analytics to drive decisions and actions. Lastly, it includes problems modeled and treated while taking into account uncertainty, risk management, behavioral issues, etc.
Book Synopsis Reinforcement Learning, second edition by : Richard S. Sutton
Download or read book Reinforcement Learning, second edition written by Richard S. Sutton and published by MIT Press. This book was released on 2018-11-13 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.
Book Synopsis Mathematics - Key Technology for the Future by : Willi Jäger
Download or read book Mathematics - Key Technology for the Future written by Willi Jäger and published by Springer Science & Business Media. This book was released on 2011-06-28 with total page 733 pages. Available in PDF, EPUB and Kindle. Book excerpt: Efficient transfer between science and society is crucial for their future development. The rapid progress of information technology and computer systems offers a large potential and new perspectives for solving complex problems. Mathematical modelling and simulation have become important tools not only in scientific investigations but also in analysing, planning and controlling technological and economic processes. Mathematics, imbedded in an interdisciplinary concept, has become a key technology. The book covers the results of a variety of major projects in industrial mathematics following an initiative of the German Federal Ministry of Education and Research. All projects are collaborations of industrial companies and university-based researchers, and range from automotive industry to computer technology and medical visualisation. In general, the projects presented in this volume prove that new mathematical ideas and methods can be decisive for the solution of industrial and economic problems.
Book Synopsis Model Free Adaptive Control by : Zhongsheng Hou
Download or read book Model Free Adaptive Control written by Zhongsheng Hou and published by CRC Press. This book was released on 2013-09-24 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model Free Adaptive Control: Theory and Applications summarizes theory and applications of model-free adaptive control (MFAC). MFAC is a novel adaptive control method for the unknown discrete-time nonlinear systems with time-varying parameters and time-varying structure, and the design and analysis of MFAC merely depend on the measured input and output data of the controlled plant, which makes it more applicable for many practical plants. This book covers new concepts, including pseudo partial derivative, pseudo gradient, pseudo Jacobian matrix, and generalized Lipschitz conditions, etc.; dynamic linearization approaches for nonlinear systems, such as compact-form dynamic linearization, partial-form dynamic linearization, and full-form dynamic linearization; a series of control system design methods, including MFAC prototype, model-free adaptive predictive control, model-free adaptive iterative learning control, and the corresponding stability analysis and typical applications in practice. In addition, some other important issues related to MFAC are also discussed. They are the MFAC for complex connected systems, the modularized controller designs between MFAC and other control methods, the robustness of MFAC, and the symmetric similarity for adaptive control system design. The book is written for researchers who are interested in control theory and control engineering, senior undergraduates and graduated students in engineering and applied sciences, as well as professional engineers in process control.
Book Synopsis Deep Learning for Sustainable Agriculture by : Ramesh Chandra Poonia
Download or read book Deep Learning for Sustainable Agriculture written by Ramesh Chandra Poonia and published by Academic Press. This book was released on 2022-01-09 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: The evolution of deep learning models, combined with with advances in the Internet of Things and sensor technology, has gained more importance for weather forecasting, plant disease detection, underground water detection, soil quality, crop condition monitoring, and many other issues in the field of agriculture. agriculture. Deep Learning for Sustainable Agriculture discusses topics such as the impactful role of deep learning during the analysis of sustainable agriculture data and how deep learning can help farmers make better decisions. It also considers the latest deep learning techniques for effective agriculture data management, as well as the standards established by international organizations in related fields. The book provides advanced students and professionals in agricultural science and engineering, geography, and geospatial technology science with an in-depth explanation of the relationship between agricultural inference and the decision-support amenities offered by an advanced mathematical evolutionary algorithm. - Introduces new deep learning models developed to address sustainable solutions for issues related to agriculture - Provides reviews on the latest intelligent technologies and algorithms related to the state-of-the-art methodologies of monitoring and mitigation of sustainable agriculture - Illustrates through case studies how deep learning has been used to address a variety of agricultural diseases that are currently on the cutting edge - Delivers an accessible explanation of artificial intelligence algorithms, making it easier for the reader to implement or use them in their own agricultural domain
