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Author: Martin Grötschel
Publisher: Springer Science & Business Media
ISBN: 3662043319
Category : Mathematics
Languages : en
Pages : 789
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Book Description
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.
Author: Martin Grötschel
Publisher: Springer Science & Business Media
ISBN: 3662043319
Category : Mathematics
Languages : en
Pages : 789
Get Book Here
Book Description
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.
Author: Pontus Giselsson
Publisher: Springer
ISBN: 3319974785
Category : Mathematics
Languages : en
Pages : 412
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Book Description
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.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 40
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Book Description
Author: Leon S. Lasdon
Publisher: Courier Corporation
ISBN: 0486143694
Category : Mathematics
Languages : en
Pages : 566
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Book Description
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.
Author: Bhadra K. Patel
Publisher:
ISBN:
Category : Linear programming
Languages : en
Pages : 798
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Book Description
Author: Lorenz T. Biegler
Publisher: Springer Science & Business Media
ISBN: 364255508X
Category : Mathematics
Languages : en
Pages : 347
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Book Description
Optimal design, optimal control, and parameter estimation of systems governed by partial differential equations (PDEs) give rise to a class of problems known as PDE-constrained optimization. The size and complexity of the discretized PDEs often pose significant challenges for contemporary optimization methods. With the maturing of technology for PDE simulation, interest has now increased in PDE-based optimization. The chapters in this volume collectively assess the state of the art in PDE-constrained optimization, identify challenges to optimization presented by modern highly parallel PDE simulation codes, and discuss promising algorithmic and software approaches for addressing them. These contributions represent current research of two strong scientific computing communities, in optimization and PDE simulation. This volume merges perspectives in these two different areas and identifies interesting open questions for further research.
Author: Y. Ho
Publisher: Springer Science & Business Media
ISBN: 1468422596
Category : Science
Languages : en
Pages : 430
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Book Description
This book is the record of papers presented at the Conference on Directions in Decentralized Control, Many-Person Optimization, and Large-Scale Systems held at the Colonial Hilton Inn, Wakefield, Massachusetts from September 1-3, 1975. Our motivation for organizing such a conference was two fold. Firstly, the last few years have seen a great deal of activity in the field of Large-Scale Systems Theory and it has been certainly one of the dominant themes of research in the disciplines of Systems and Control Theory. It therefore seemed appropriate to try and take stock of what had been accomplished and also try to "invent"l the future directions of research in this field. Secondly, the 6th World IFAC Conference was being held in Cambridge, Massachusetts the week earlier and it provided an ideal opportunity for taking advantage of the presence of a large number of specialists from all parts of the world to organize a small conference where a free exchange of ideas could take place. It is left to the readers of this volume to judge to what extent we have been successful in our above mentioned goals. There is no accepted definition of what constitutes a "large scale system" nor what large-scale system theory is. While this diversity does suggest that the field {whatever it may turn out to be} is in a state of flux, it does not necessarily imply chaos.
Author: Haoyong Chen
Publisher: John Wiley & Sons
ISBN: 1118724771
Category : Technology & Engineering
Languages : en
Pages : 392
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Book Description
An original look from a microeconomic perspective for power system optimization and its application to electricity markets Presents a new and systematic viewpoint for power system optimization inspired by microeconomics and game theory A timely and important advanced reference with the fast growth of smart grids Professor Chen is a pioneer of applying experimental economics to the electricity market trading mechanism, and this work brings together the latest research A companion website is available Edit
Author: Vinod Kumar Chauhan
Publisher: CRC Press
ISBN: 1000505618
Category : Computers
Languages : en
Pages : 189
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Book Description
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.
Author: Richard Kipp Martin
Publisher: Springer Science & Business Media
ISBN: 1461549752
Category : Business & Economics
Languages : en
Pages : 739
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Book Description
This is a textbook about linear and integer linear optimization. There is a growing need in industries such as airline, trucking, and financial engineering to solve very large linear and integer linear optimization problems. Building these models requires uniquely trained individuals. Not only must they have a thorough understanding of the theory behind mathematical programming, they must have substantial knowledge of how to solve very large models in today's computing environment. The major goal of the book is to develop the theory of linear and integer linear optimization in a unified manner and then demonstrate how to use this theory in a modern computing environment to solve very large real world problems. After presenting introductory material in Part I, Part II of this book is de voted to the theory of linear and integer linear optimization. This theory is developed using two simple, but unifying ideas: projection and inverse projec tion. Through projection we take a system of linear inequalities and replace some of the variables with additional linear inequalities. Inverse projection, the dual of this process, involves replacing linear inequalities with additional variables. Fundamental results such as weak and strong duality, theorems of the alternative, complementary slackness, sensitivity analysis, finite basis the orems, etc. are all explained using projection or inverse projection. Indeed, a unique feature of this book is that these fundamental results are developed and explained before the simplex and interior point algorithms are presented.
