Large-scale Optimization

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Publisher : Springer Science & Business Media
ISBN 13 : 1475732430
Total Pages : 322 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Large-scale Optimization by : Vladimir Tsurkov

Download or read book Large-scale Optimization written by Vladimir Tsurkov and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decomposition methods aim to reduce large-scale problems to simpler problems. This monograph presents selected aspects of the dimension-reduction problem. Exact and approximate aggregations of multidimensional systems are developed and from a known model of input-output balance, aggregation methods are categorized. The issues of loss of accuracy, recovery of original variables (disaggregation), and compatibility conditions are analyzed in detail. The method of iterative aggregation in large-scale problems is studied. For fixed weights, successively simpler aggregated problems are solved and the convergence of their solution to that of the original problem is analyzed. An introduction to block integer programming is considered. Duality theory, which is widely used in continuous block programming, does not work for the integer problem. A survey of alternative methods is presented and special attention is given to combined methods of decomposition. Block problems in which the coupling variables do not enter the binding constraints are studied. These models are worthwhile because they permit a decomposition with respect to primal and dual variables by two-level algorithms instead of three-level algorithms. Audience: This book is addressed to specialists in operations research, optimization, and optimal control.

Large-Scale and Distributed Optimization

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Publisher : Springer
ISBN 13 : 3319974785
Total Pages : 412 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Large-Scale and Distributed Optimization by : Pontus Giselsson

Download or read book Large-Scale and Distributed Optimization written by Pontus Giselsson and published by Springer. This book was released on 2018-11-11 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents tools and methods for large-scale and distributed optimization. Since many methods in "Big Data" fields rely on solving large-scale optimization problems, often in distributed fashion, this topic has over the last decade emerged to become very important. As well as specific coverage of this active research field, the book serves as a powerful source of information for practitioners as well as theoreticians. Large-Scale and Distributed Optimization is a unique combination of contributions from leading experts in the field, who were speakers at the LCCC Focus Period on Large-Scale and Distributed Optimization, held in Lund, 14th–16th June 2017. A source of information and innovative ideas for current and future research, this book will appeal to researchers, academics, and students who are interested in large-scale optimization.

Large Scale Optimization in Supply Chains and Smart Manufacturing

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Publisher : Springer Nature
ISBN 13 : 303022788X
Total Pages : 282 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Large Scale Optimization in Supply Chains and Smart Manufacturing by : Jesús M. Velásquez-Bermúdez

Download or read book Large Scale Optimization in Supply Chains and Smart Manufacturing written by Jesús M. Velásquez-Bermúdez and published by Springer Nature. This book was released on 2019-09-06 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, theory of large scale optimization is introduced with case studies of real-world problems and applications of structured mathematical modeling. The large scale optimization methods are represented by various theories such as Benders’ decomposition, logic-based Benders’ decomposition, Lagrangian relaxation, Dantzig –Wolfe decomposition, multi-tree decomposition, Van Roy’ cross decomposition and parallel decomposition for mathematical programs such as mixed integer nonlinear programming and stochastic programming. Case studies of large scale optimization in supply chain management, smart manufacturing, and Industry 4.0 are investigated with efficient implementation for real-time solutions. The features of case studies cover a wide range of fields including the Internet of things, advanced transportation systems, energy management, supply chain networks, service systems, operations management, risk management, and financial and sales management. Instructors, graduate students, researchers, and practitioners, would benefit from this book finding the applicability of large scale optimization in asynchronous parallel optimization, real-time distributed network, and optimizing the knowledge-based expert system for convex and non-convex problems.

Optimization in Large Scale Problems

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Publisher : Springer Nature
ISBN 13 : 3030285650
Total Pages : 333 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Optimization in Large Scale Problems by : Mahdi Fathi

Download or read book Optimization in Large Scale Problems written by Mahdi Fathi and published by Springer Nature. This book was released on 2019-11-20 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides resourceful thinking and insightful management solutions to the many challenges that decision makers face in their predictions, preparations, and implementations of the key elements that our societies and industries need to take as they move toward digitalization and smartness. The discussions within the book aim to uncover the sources of large-scale problems in socio-industrial dilemmas, and the theories that can support these challenges. How theories might also transition to real applications is another question that this book aims to uncover. In answer to the viewpoints expressed by several practitioners and academicians, this book aims to provide both a learning platform which spotlights open questions with related case studies. The relationship between Industry 4.0 and Society 5.0 provides the basis for the expert contributions in this book, highlighting the uses of analytical methods such as mathematical optimization, heuristic methods, decomposition methods, stochastic optimization, and more. The book will prove useful to researchers, students, and engineers in different domains who encounter large scale optimization problems and will encourage them to undertake research in this timely and practical field. The book splits into two parts. The first part covers a general perspective and challenges in a smart society and in industry. The second part covers several case studies and solutions from the operations research perspective for large scale challenges specific to various industry and society related phenomena.

Optimization Theory for Large Systems

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Publisher : Courier Corporation
ISBN 13 : 0486143694
Total Pages : 566 pages
Book Rating : 4.4/5 (861 download)

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Book Synopsis Optimization Theory for Large Systems by : Leon S. Lasdon

Download or read book Optimization Theory for Large Systems written by Leon S. Lasdon and published by Courier Corporation. This book was released on 2013-01-17 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: Important text examines most significant algorithms for optimizing large systems and clarifying relations between optimization procedures. Much data appear as charts and graphs and will be highly valuable to readers in selecting a method and estimating computer time and cost in problem-solving. Initial chapter on linear and nonlinear programming presents all necessary background for subjects covered in rest of book. Second chapter illustrates how large-scale mathematical programs arise from real-world problems. Appendixes. List of Symbols.

Studies in Large-scale Optimization

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Publisher :
ISBN 13 :
Total Pages : 280 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Studies in Large-scale Optimization by : Chih-Jen Lin

Download or read book Studies in Large-scale Optimization written by Chih-Jen Lin and published by . This book was released on 1998 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Big Data Optimization: Recent Developments and Challenges

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Publisher : Springer
ISBN 13 : 3319302655
Total Pages : 492 pages
Book Rating : 4.3/5 (193 download)

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Book Synopsis Big Data Optimization: Recent Developments and Challenges by : Ali Emrouznejad

Download or read book Big Data Optimization: Recent Developments and Challenges written by Ali Emrouznejad and published by Springer. This book was released on 2016-05-26 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main objective of this book is to provide the necessary background to work with big data by introducing some novel optimization algorithms and codes capable of working in the big data setting as well as introducing some applications in big data optimization for both academics and practitioners interested, and to benefit society, industry, academia, and government. Presenting applications in a variety of industries, this book will be useful for the researchers aiming to analyses large scale data. Several optimization algorithms for big data including convergent parallel algorithms, limited memory bundle algorithm, diagonal bundle method, convergent parallel algorithms, network analytics, and many more have been explored in this book.

Large Scale Optimization

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Publisher : Springer Science & Business Media
ISBN 13 : 1461336325
Total Pages : 470 pages
Book Rating : 4.4/5 (613 download)

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Book Synopsis Large Scale Optimization by : William W. Hager

Download or read book Large Scale Optimization written by William W. Hager and published by Springer Science & Business Media. This book was released on 2013-12-01 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: On February 15-17, 1993, a conference on Large Scale Optimization, hosted by the Center for Applied Optimization, was held at the University of Florida. The con ference was supported by the National Science Foundation, the U. S. Army Research Office, and the University of Florida, with endorsements from SIAM, MPS, ORSA and IMACS. Forty one invited speakers presented papers on mathematical program ming and optimal control topics with an emphasis on algorithm development, real world applications and numerical results. Participants from Canada, Japan, Sweden, The Netherlands, Germany, Belgium, Greece, and Denmark gave the meeting an important international component. At tendees also included representatives from IBM, American Airlines, US Air, United Parcel Serice, AT & T Bell Labs, Thinking Machines, Army High Performance Com puting Research Center, and Argonne National Laboratory. In addition, the NSF sponsored attendance of thirteen graduate students from universities in the United States and abroad. Accurate modeling of scientific problems often leads to the formulation of large scale optimization problems involving thousands of continuous and/or discrete vari ables. Large scale optimization has seen a dramatic increase in activities in the past decade. This has been a natural consequence of new algorithmic developments and of the increased power of computers. For example, decomposition ideas proposed by G. Dantzig and P. Wolfe in the 1960's, are now implement able in distributed process ing systems, and today many optimization codes have been implemented on parallel machines.

Large-Scale Convex Optimization

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Publisher : Cambridge University Press
ISBN 13 : 1009191063
Total Pages : 320 pages
Book Rating : 4.0/5 (91 download)

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Book Synopsis Large-Scale Convex Optimization by : Ernest K. Ryu

Download or read book Large-Scale Convex Optimization written by Ernest K. Ryu and published by Cambridge University Press. This book was released on 2022-12-01 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Starting from where a first course in convex optimization leaves off, this text presents a unified analysis of first-order optimization methods – including parallel-distributed algorithms – through the abstraction of monotone operators. With the increased computational power and availability of big data over the past decade, applied disciplines have demanded that larger and larger optimization problems be solved. This text covers the first-order convex optimization methods that are uniquely effective at solving these large-scale optimization problems. Readers will have the opportunity to construct and analyze many well-known classical and modern algorithms using monotone operators, and walk away with a solid understanding of the diverse optimization algorithms. Graduate students and researchers in mathematical optimization, operations research, electrical engineering, statistics, and computer science will appreciate this concise introduction to the theory of convex optimization algorithms.

Stochastic Optimization for Large-scale Machine Learning

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Publisher : CRC Press
ISBN 13 : 1000505537
Total Pages : 177 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis Stochastic Optimization for Large-scale Machine Learning by : Vinod Kumar Chauhan

Download or read book Stochastic Optimization for Large-scale Machine Learning written by Vinod Kumar Chauhan and published by CRC Press. This book was released on 2021-11-18 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advancements in the technology and availability of data sources have led to the `Big Data' era. Working with large data offers the potential to uncover more fine-grained patterns and take timely and accurate decisions, but it also creates a lot of challenges such as slow training and scalability of machine learning models. One of the major challenges in machine learning is to develop efficient and scalable learning algorithms, i.e., optimization techniques to solve large scale learning problems. Stochastic Optimization for Large-scale Machine Learning identifies different areas of improvement and recent research directions to tackle the challenge. Developed optimisation techniques are also explored to improve machine learning algorithms based on data access and on first and second order optimisation methods. Key Features: Bridges machine learning and Optimisation. Bridges theory and practice in machine learning. Identifies key research areas and recent research directions to solve large-scale machine learning problems. Develops optimisation techniques to improve machine learning algorithms for big data problems. The book will be a valuable reference to practitioners and researchers as well as students in the field of machine learning.

Large-Scale Nonlinear Optimization

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Publisher : Springer Science & Business Media
ISBN 13 : 0387300651
Total Pages : 297 pages
Book Rating : 4.3/5 (873 download)

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Book Synopsis Large-Scale Nonlinear Optimization by : Gianni Pillo

Download or read book Large-Scale Nonlinear Optimization written by Gianni Pillo and published by Springer Science & Business Media. This book was released on 2006-06-03 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews and discusses recent advances in the development of methods and algorithms for nonlinear optimization and its applications, focusing on the large-dimensional case, the current forefront of much research. Individual chapters, contributed by eminent authorities, provide an up-to-date overview of the field from different and complementary standpoints, including theoretical analysis, algorithmic development, implementation issues and applications.

Optimization for Machine Learning

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Publisher : MIT Press
ISBN 13 : 026201646X
Total Pages : 509 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Optimization for Machine Learning by : Suvrit Sra

Download or read book Optimization for Machine Learning written by Suvrit Sra and published by MIT Press. This book was released on 2012 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay between optimization and machine learning is one of the most important developments in modern computational science. Optimization formulations and methods are proving to be vital in designing algorithms to extract essential knowledge from huge volumes of data. Machine learning, however, is not simply a consumer of optimization technology but a rapidly evolving field that is itself generating new optimization ideas. This book captures the state of the art of the interaction between optimization and machine learning in a way that is accessible to researchers in both fields. Optimization approaches have enjoyed prominence in machine learning because of their wide applicability and attractive theoretical properties. The increasing complexity, size, and variety of today's machine learning models call for the reassessment of existing assumptions. This book starts the process of reassessment. It describes the resurgence in novel contexts of established frameworks such as first-order methods, stochastic approximations, convex relaxations, interior-point methods, and proximal methods. It also devotes attention to newer themes such as regularized optimization, robust optimization, gradient and subgradient methods, splitting techniques, and second-order methods. Many of these techniques draw inspiration from other fields, including operations research, theoretical computer science, and subfields of optimization. The book will enrich the ongoing cross-fertilization between the machine learning community and these other fields, and within the broader optimization community.

Large-scale Optimization with Applications

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Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (875 download)

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Book Synopsis Large-scale Optimization with Applications by : Lorenz T. Biegler

Download or read book Large-scale Optimization with Applications written by Lorenz T. Biegler and published by . This book was released on with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Large-Scale Optimization with Applications

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Publisher : Springer Science & Business Media
ISBN 13 : 9780387982878
Total Pages : 354 pages
Book Rating : 4.9/5 (828 download)

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Book Synopsis Large-Scale Optimization with Applications by :

Download or read book Large-Scale Optimization with Applications written by and published by Springer Science & Business Media. This book was released on 1997 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Large-Scale Nonlinear Optimization

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Publisher : Springer
ISBN 13 : 9780387510668
Total Pages : 0 pages
Book Rating : 4.5/5 (16 download)

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Book Synopsis Large-Scale Nonlinear Optimization by : Gianni Pillo

Download or read book Large-Scale Nonlinear Optimization written by Gianni Pillo and published by Springer. This book was released on 2008-11-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews and discusses recent advances in the development of methods and algorithms for nonlinear optimization and its applications, focusing on the large-dimensional case, the current forefront of much research. Individual chapters, contributed by eminent authorities, provide an up-to-date overview of the field from different and complementary standpoints, including theoretical analysis, algorithmic development, implementation issues and applications.

Online Optimization of Large Scale Systems

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Publisher : Springer Science & Business Media
ISBN 13 : 3662043319
Total Pages : 789 pages
Book Rating : 4.6/5 (62 download)

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Book Synopsis Online Optimization of Large Scale Systems by : Martin Grötschel

Download or read book Online Optimization of Large Scale Systems written by Martin Grötschel and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 789 pages. Available in PDF, EPUB and Kindle. Book excerpt: In its thousands of years of history, mathematics has made an extraordinary ca reer. It started from rules for bookkeeping and computation of areas to become the language of science. Its potential for decision support was fully recognized in the twentieth century only, vitally aided by the evolution of computing and communi cation technology. Mathematical optimization, in particular, has developed into a powerful machinery to help planners. Whether costs are to be reduced, profits to be maximized, or scarce resources to be used wisely, optimization methods are available to guide decision making. Opti mization is particularly strong if precise models of real phenomena and data of high quality are at hand - often yielding reliable automated control and decision proce dures. But what, if the models are soft and not all data are around? Can mathematics help as well? This book addresses such issues, e. g. , problems of the following type: - An elevator cannot know all transportation requests in advance. In which order should it serve the passengers? - Wing profiles of aircrafts influence the fuel consumption. Is it possible to con tinuously adapt the shape of a wing during the flight under rapidly changing conditions? - Robots are designed to accomplish specific tasks as efficiently as possible. But what if a robot navigates in an unknown environment? - Energy demand changes quickly and is not easily predictable over time. Some types of power plants can only react slowly.

Large-scale Optimization with Applications: Optimal design and control

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Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (97 download)

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Book Synopsis Large-scale Optimization with Applications: Optimal design and control by :

Download or read book Large-scale Optimization with Applications: Optimal design and control written by and published by . This book was released on 1997 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: