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Bonus Algorithm For Large Scale Stochastic Nonlinear Programming Problems

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Bonus Algorithm For Large Scale Stochastic Nonlinear Programming Problems

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Author : Urmila Diwekar
language : en
Publisher: Springer
Release Date : 2015-03-05

Bonus Algorithm For Large Scale Stochastic Nonlinear Programming Problems written by Urmila Diwekar and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-05 with Business & Economics categories.

This book presents the details of the BONUS algorithm and its real world applications in areas like sensor placement in large scale drinking water networks, sensor placement in advanced power systems, water management in power systems, and capacity expansion of energy systems. A generalized method for stochastic nonlinear programming based on a sampling based approach for uncertainty analysis and statistical reweighting to obtain probability information is demonstrated in this book. Stochastic optimization problems are difficult to solve since they involve dealing with optimization and uncertainty loops. There are two fundamental approaches used to solve such problems. The first being the decomposition techniques and the second method identifies problem specific structures and transforms the problem into a deterministic nonlinear programming problem. These techniques have significant limitations on either the objective function type or the underlying distributions for the uncertain variables. Moreover, these methods assume that there are a small number of scenarios to be evaluated for calculation of the probabilistic objective function and constraints. This book begins to tackle these issues by describing a generalized method for stochastic nonlinear programming problems. This title is best suited for practitioners, researchers and students in engineering, operations research, and management science who desire a complete understanding of the BONUS algorithm and its applications to the real world.

Stochastic Decomposition

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Author : Julia L. Higle
language : en
Publisher: Springer Science & Business Media
Release Date : 1996-02-29

Stochastic Decomposition written by Julia L. Higle and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-02-29 with Business & Economics categories.

This book summarizes developments related to a class of methods called Stochastic Decomposition (SD) algorithms, which represent an important shift in the design of optimization algorithms. Unlike traditional deterministic algorithms, SD combines sampling approaches from the statistical literature with traditional mathematical programming constructs (e.g. decomposition, cutting planes etc.). This marriage of two highly computationally oriented disciplines leads to a line of work that is most definitely driven by computational considerations. Furthermore, the use of sampled data in SD makes it extremely flexible in its ability to accommodate various representations of uncertainty, including situations in which outcomes/scenarios can only be generated by an algorithm/simulation. The authors report computational results with some of the largest stochastic programs arising in applications. These results (mathematical as well as computational) are the `tip of the iceberg'. Further research will uncover extensions of SD to a wider class of problems. Audience: Researchers in mathematical optimization, including those working in telecommunications, electric power generation, transportation planning, airlines and production systems. Also suitable as a text for an advanced course in stochastic optimization.

Life Cycle Analysis Of Nanoparticles

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Author : Ashok Vaseashta
language : en
Publisher: DEStech Publications, Inc
Release Date : 2015-03-30

Life Cycle Analysis Of Nanoparticles written by Ashok Vaseashta and has been published by DEStech Publications, Inc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-30 with Technology & Engineering categories.

Investigative tools for analyzing environmental nanoparticles with health impactsBasic theories and models of life cycle analysis applied to nanomaterialsConnects LCA, detection technologies and sustainability This book addresses the ways life cycle assessment (LCA) concepts can be applied to analyze the fate of nanoparticles in a variety of environmental and manufacturing settings. After introducing LCA theory and modeling concepts, the work discusses risks associated with carbon nanotubes, graphene, silver, fullerenes, iron oxides and other particles generated by manufacturing or medical diagnostics. Chapters in the text discuss biomolecules and the application of in vivo biosensors. Also covered are fate analysis, risk assessment, toxicology and nanopathology with a focus on human health and disease.

Stochastic Linear Programming Algorithms

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Author : Janos Mayer
language : en
Publisher: CRC Press
Release Date : 1998-02-25

Stochastic Linear Programming Algorithms written by Janos Mayer and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-02-25 with Computers categories.

A computationally oriented comparison of solution algorithms for two stage and jointly chance constrained stochastic linear programming problems, this is the first book to present comparative computational results with several major stochastic programming solution approaches. The following methods are considered: regularized decomposition, stochastic decomposition and successive discrete approximation methods for two stage problems; cutting plane methods, and a reduced gradient method for jointly chance constrained problems. The first part of the book introduces the algorithms, including a unified approach to decomposition methods and their regularized counterparts. The second part addresses computer implementation of the methods, describes a testing environment based on a model management system, and presents comparative computational results with the various algorithms. Emphasis is on the computational behavior of the algorithms.

Stochastic Programming Algorithms And Models

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Author : Julia L. Higle
language : en
Publisher:
Release Date : 1996

Stochastic Programming Algorithms And Models written by Julia L. Higle and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Mathematical optimization categories.

Stochastic Linear Programming Algorithms

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Author : Janos Mayer
language : en
Publisher: Taylor & Francis
Release Date : 2022-04-19

Stochastic Linear Programming Algorithms written by Janos Mayer and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-19 with Computers categories.

Applications Of Stochastic Programming

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Author : Stein W. Wallace
language : en
Publisher: SIAM
Release Date : 2005-06-01

Applications Of Stochastic Programming written by Stein W. Wallace and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-06-01 with Mathematics categories.

Consisting of two parts, this book presents papers describing publicly available stochastic programming systems that are operational. It presents a diverse collection of application papers in areas such as production, supply chain and scheduling, gaming, environmental and pollution control, financial modeling, telecommunications, and electricity.

Informs Annual Meeting

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Author : Institute for Operations Research and the Management Sciences. National Meeting
language : en
Publisher:
Release Date : 2009

Informs Annual Meeting written by Institute for Operations Research and the Management Sciences. National Meeting and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Industrial management categories.

Nonlinear Programming And Variational Inequality Problems

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Author : Michael Patriksson
language : en
Publisher: Springer Science & Business Media
Release Date : 1999

Nonlinear Programming And Variational Inequality Problems written by Michael Patriksson and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Business & Economics categories.

The framework of algorithms presented in this book is called Cost Approximation. It describes, for a given formulation of a variational inequality or nonlinear programming problem, an algorithm by means of approximating mappings and problems, a principle for the updating of the iteration points, and a merit function which guides and monitors the convergence of the algorithm. One purpose of the book is to offer this framework as an intuitively appealing tool for describing an algorithm. Another purpose is to provide a convergence analysis of the algorithms in the framework. Audience: The book will be of interest to all researchers in the field (it includes over 800 references) and can also be used for advanced courses in non-linear optimization with the possibility of being oriented either to algorithm theory or to the numerical aspects of large-scale nonlinear optimization.

Large Scale Optimization

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Author : Vladimir Tsurkov
language : en
Publisher: Springer Science & Business Media
Release Date : 2001-03-31

Large Scale Optimization written by Vladimir Tsurkov and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-03-31 with Computers categories.

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.

Bonus Algorithm For Large Scale Stochastic Nonlinear Programming Problems

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