Nonlinear Optimization Applications Using the GAMS Technology

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Publisher : Springer Science & Business Media
ISBN 13 : 1461467977
Total Pages : 356 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Nonlinear Optimization Applications Using the GAMS Technology by : Neculai Andrei

Download or read book Nonlinear Optimization Applications Using the GAMS Technology written by Neculai Andrei and published by Springer Science & Business Media. This book was released on 2013-06-22 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Here is a collection of nonlinear optimization applications from the real world, expressed in the General Algebraic Modeling System (GAMS). The concepts are presented so that the reader can quickly modify and update them to represent real-world situations.

Continuous Nonlinear Optimization for Engineering Applications in GAMS Technology

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Publisher : Springer
ISBN 13 : 3319583565
Total Pages : 514 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Continuous Nonlinear Optimization for Engineering Applications in GAMS Technology by : Neculai Andrei

Download or read book Continuous Nonlinear Optimization for Engineering Applications in GAMS Technology written by Neculai Andrei and published by Springer. This book was released on 2017-12-04 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the theoretical details and computational performances of algorithms used for solving continuous nonlinear optimization applications imbedded in GAMS. Aimed toward scientists and graduate students who utilize optimization methods to model and solve problems in mathematical programming, operations research, business, engineering, and industry, this book enables readers with a background in nonlinear optimization and linear algebra to use GAMS technology to understand and utilize its important capabilities to optimize algorithms for modeling and solving complex, large-scale, continuous nonlinear optimization problems or applications. Beginning with an overview of constrained nonlinear optimization methods, this book moves on to illustrate key aspects of mathematical modeling through modeling technologies based on algebraically oriented modeling languages. Next, the main feature of GAMS, an algebraically oriented language that allows for high-level algebraic representation of mathematical optimization models, is introduced to model and solve continuous nonlinear optimization applications. More than 15 real nonlinear optimization applications in algebraic and GAMS representation are presented which are used to illustrate the performances of the algorithms described in this book. Theoretical and computational results, methods, and techniques effective for solving nonlinear optimization problems, are detailed through the algorithms MINOS, KNITRO, CONOPT, SNOPT and IPOPT which work in GAMS technology.

Modern Numerical Nonlinear Optimization

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Publisher : Springer Nature
ISBN 13 : 3031087208
Total Pages : 824 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Modern Numerical Nonlinear Optimization by : Neculai Andrei

Download or read book Modern Numerical Nonlinear Optimization written by Neculai Andrei and published by Springer Nature. This book was released on 2022-10-18 with total page 824 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes a thorough theoretical and computational analysis of unconstrained and constrained optimization algorithms and combines and integrates the most recent techniques and advanced computational linear algebra methods. Nonlinear optimization methods and techniques have reached their maturity and an abundance of optimization algorithms are available for which both the convergence properties and the numerical performances are known. This clear, friendly, and rigorous exposition discusses the theory behind the nonlinear optimization algorithms for understanding their properties and their convergence, enabling the reader to prove the convergence of his/her own algorithms. It covers cases and computational performances of the most known modern nonlinear optimization algorithms that solve collections of unconstrained and constrained optimization test problems with different structures, complexities, as well as those with large-scale real applications. The book is addressed to all those interested in developing and using new advanced techniques for solving large-scale unconstrained or constrained complex optimization problems. Mathematical programming researchers, theoreticians and practitioners in operations research, practitioners in engineering and industry researchers, as well as graduate students in mathematics, Ph.D. and master in mathematical programming will find plenty of recent information and practical approaches for solving real large-scale optimization problems and applications.

A Derivative-free Two Level Random Search Method for Unconstrained Optimization

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Publisher : Springer Nature
ISBN 13 : 3030685179
Total Pages : 126 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis A Derivative-free Two Level Random Search Method for Unconstrained Optimization by : Neculai Andrei

Download or read book A Derivative-free Two Level Random Search Method for Unconstrained Optimization written by Neculai Andrei and published by Springer Nature. This book was released on 2021-03-31 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is intended for graduate students and researchers in mathematics, computer science, and operational research. The book presents a new derivative-free optimization method/algorithm based on randomly generated trial points in specified domains and where the best ones are selected at each iteration by using a number of rules. This method is different from many other well established methods presented in the literature and proves to be competitive for solving many unconstrained optimization problems with different structures and complexities, with a relative large number of variables. Intensive numerical experiments with 140 unconstrained optimization problems, with up to 500 variables, have shown that this approach is efficient and robust. Structured into 4 chapters, Chapter 1 is introductory. Chapter 2 is dedicated to presenting a two level derivative-free random search method for unconstrained optimization. It is assumed that the minimizing function is continuous, lower bounded and its minimum value is known. Chapter 3 proves the convergence of the algorithm. In Chapter 4, the numerical performances of the algorithm are shown for solving 140 unconstrained optimization problems, out of which 16 are real applications. This shows that the optimization process has two phases: the reduction phase and the stalling one. Finally, the performances of the algorithm for solving a number of 30 large-scale unconstrained optimization problems up to 500 variables are presented. These numerical results show that this approach based on the two level random search method for unconstrained optimization is able to solve a large diversity of problems with different structures and complexities. There are a number of open problems which refer to the following aspects: the selection of the number of trial or the number of the local trial points, the selection of the bounds of the domains where the trial points and the local trial points are randomly generated and a criterion for initiating the line search.

Nonlinear Conjugate Gradient Methods for Unconstrained Optimization

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Publisher : Springer Nature
ISBN 13 : 3030429504
Total Pages : 515 pages
Book Rating : 4.0/5 (34 download)

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Book Synopsis Nonlinear Conjugate Gradient Methods for Unconstrained Optimization by : Neculai Andrei

Download or read book Nonlinear Conjugate Gradient Methods for Unconstrained Optimization written by Neculai Andrei and published by Springer Nature. This book was released on 2020-06-23 with total page 515 pages. Available in PDF, EPUB and Kindle. Book excerpt: Two approaches are known for solving large-scale unconstrained optimization problems—the limited-memory quasi-Newton method (truncated Newton method) and the conjugate gradient method. This is the first book to detail conjugate gradient methods, showing their properties and convergence characteristics as well as their performance in solving large-scale unconstrained optimization problems and applications. Comparisons to the limited-memory and truncated Newton methods are also discussed. Topics studied in detail include: linear conjugate gradient methods, standard conjugate gradient methods, acceleration of conjugate gradient methods, hybrid, modifications of the standard scheme, memoryless BFGS preconditioned, and three-term. Other conjugate gradient methods with clustering the eigenvalues or with the minimization of the condition number of the iteration matrix, are also treated. For each method, the convergence analysis, the computational performances and the comparisons versus other conjugate gradient methods are given. The theory behind the conjugate gradient algorithms presented as a methodology is developed with a clear, rigorous, and friendly exposition; the reader will gain an understanding of their properties and their convergence and will learn to develop and prove the convergence of his/her own methods. Numerous numerical studies are supplied with comparisons and comments on the behavior of conjugate gradient algorithms for solving a collection of 800 unconstrained optimization problems of different structures and complexities with the number of variables in the range [1000,10000]. The book is addressed to all those interested in developing and using new advanced techniques for solving unconstrained optimization complex problems. Mathematical programming researchers, theoreticians and practitioners in operations research, practitioners in engineering and industry researchers, as well as graduate students in mathematics, Ph.D. and master students in mathematical programming, will find plenty of information and practical applications for solving large-scale unconstrained optimization problems and applications by conjugate gradient methods.

Power System Optimization Modeling in GAMS

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Publisher : Springer
ISBN 13 : 3319623508
Total Pages : 309 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Power System Optimization Modeling in GAMS by : Alireza Soroudi

Download or read book Power System Optimization Modeling in GAMS written by Alireza Soroudi and published by Springer. This book was released on 2017-08-29 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique book describes how the General Algebraic Modeling System (GAMS) can be used to solve various power system operation and planning optimization problems. This book is the first of its kind to provide readers with a comprehensive reference that includes the solution codes for basic/advanced power system optimization problems in GAMS, a computationally efficient tool for analyzing optimization problems in power and energy systems. The book covers theoretical background as well as the application examples and test case studies. It is a suitable reference for dedicated and general audiences including power system professionals as well as researchers and developers from the energy sector and electrical power engineering community and will be helpful to undergraduate and graduate students.

GAMS

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Author :
Publisher : Course Technology
ISBN 13 :
Total Pages : 314 pages
Book Rating : 4.E/5 ( download)

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Book Synopsis GAMS by : Anthony Brooke

Download or read book GAMS written by Anthony Brooke and published by Course Technology. This book was released on 1992 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Global Optimization in Engineering Design

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Publisher : Springer Science & Business Media
ISBN 13 : 1475753314
Total Pages : 390 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Global Optimization in Engineering Design by : Ignacio E. Grossmann

Download or read book Global Optimization in Engineering Design written by Ignacio E. Grossmann and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Programming has been of significant interest and relevance in engineering, an area that is very rich in challenging optimization problems. In particular, many design and operational problems give rise to nonlinear and mixed-integer nonlinear optimization problems whose modeling and solu tion is often nontrivial. Furthermore, with the increased computational power and development of advanced analysis (e. g. , process simulators, finite element packages) and modeling systems (e. g. , GAMS, AMPL, SPEEDUP, ASCEND, gPROMS), the size and complexity of engineering optimization models is rapidly increasing. While the application of efficient local solvers (nonlinear program ming algorithms) has become widespread, a major limitation is that there is often no guarantee that the solutions that are generated correspond to global optima. In some cases finding a local solution might be adequate, but in others it might mean incurring a significant cost penalty, or even worse, getting an incorrect solution to a physical problem. Thus, the need for finding global optima in engineering is a very real one. It is the purpose of this monograph to present recent developments of tech niques and applications of deterministic approaches to global optimization in engineering. The present monograph is heavily represented by chemical engi neers; and to a large extent this is no accident. The reason is that mathematical programming is an active and vibrant area of research in chemical engineering. This trend has existed for about 15 years.

Optimization and Approximation

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Publisher : Springer
ISBN 13 : 3319648438
Total Pages : 261 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Optimization and Approximation by : Pablo Pedregal

Download or read book Optimization and Approximation written by Pablo Pedregal and published by Springer. This book was released on 2017-09-07 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a basic, initial resource, introducing science and engineering students to the field of optimization. It covers three main areas: mathematical programming, calculus of variations and optimal control, highlighting the ideas and concepts and offering insights into the importance of optimality conditions in each area. It also systematically presents affordable approximation methods. Exercises at various levels have been included to support the learning process.

Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming

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Publisher : Springer Science & Business Media
ISBN 13 : 1475735324
Total Pages : 492 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming by : Mohit Tawarmalani

Download or read book Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming written by Mohit Tawarmalani and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interest in constrained optimization originated with the simple linear pro gramming model since it was practical and perhaps the only computationally tractable model at the time. Constrained linear optimization models were soon adopted in numerous application areas and are perhaps the most widely used mathematical models in operations research and management science at the time of this writing. Modelers have, however, found the assumption of linearity to be overly restrictive in expressing the real-world phenomena and problems in economics, finance, business, communication, engineering design, computational biology, and other areas that frequently demand the use of nonlinear expressions and discrete variables in optimization models. Both of these extensions of the linear programming model are NP-hard, thus representing very challenging problems. On the brighter side, recent advances in algorithmic and computing technology make it possible to re visit these problems with the hope of solving practically relevant problems in reasonable amounts of computational time. Initial attempts at solving nonlinear programs concentrated on the de velopment of local optimization methods guaranteeing globality under the assumption of convexity. On the other hand, the integer programming liter ature has concentrated on the development of methods that ensure global optima. The aim of this book is to marry the advancements in solving nonlinear and integer programming models and to develop new results in the more general framework of mixed-integer nonlinear programs (MINLPs) with the goal of devising practically efficient global optimization algorithms for MINLPs.

Business Optimization Using Mathematical Programming

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Publisher : Springer Nature
ISBN 13 : 3030732371
Total Pages : 653 pages
Book Rating : 4.0/5 (37 download)

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Book Synopsis Business Optimization Using Mathematical Programming by : Josef Kallrath

Download or read book Business Optimization Using Mathematical Programming written by Josef Kallrath and published by Springer Nature. This book was released on 2021-08-31 with total page 653 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a structured approach to formulate, model, and solve mathematical optimization problems for a wide range of real world situations. Among the problems covered are production, distribution and supply chain planning, scheduling, vehicle routing, as well as cutting stock, packing, and nesting. The optimization techniques used to solve the problems are primarily linear, mixed-integer linear, nonlinear, and mixed integer nonlinear programming. The book also covers important considerations for solving real-world optimization problems, such as dealing with valid inequalities and symmetry during the modeling phase, but also data interfacing and visualization of results in a more and more digitized world. The broad range of ideas and approaches presented helps the reader to learn how to model a variety of problems from process industry, paper and metals industry, the energy sector, and logistics using mathematical optimization techniques.

GAMS, a User's Guide

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Publisher : Course Technology
ISBN 13 :
Total Pages : 310 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis GAMS, a User's Guide by : Anthony Brooke

Download or read book GAMS, a User's Guide written by Anthony Brooke and published by Course Technology. This book was released on 1988 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Smart Applications with Advanced Machine Learning and Human-Centred Problem Design

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Publisher : Springer Nature
ISBN 13 : 303109753X
Total Pages : 801 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Smart Applications with Advanced Machine Learning and Human-Centred Problem Design by : D. Jude Hemanth

Download or read book Smart Applications with Advanced Machine Learning and Human-Centred Problem Design written by D. Jude Hemanth and published by Springer Nature. This book was released on 2023-01-01 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together the most recent, quality research papers accepted and presented in the 3rd International Conference on Artificial Intelligence and Applied Mathematics in Engineering (ICAIAME 2021) held in Antalya, Turkey between 1-3 October 2021. Objective of the content is to provide important and innovative research for developments-improvements within different engineering fields, which are highly interested in using artificial intelligence and applied mathematics. As a collection of the outputs from the ICAIAME 2021, the book is specifically considering research outcomes including advanced use of machine learning and careful problem designs on human-centred aspects. In this context, it aims to provide recent applications for real-world improvements making life easier and more sustainable for especially humans. The book targets the researchers, degree students, and practitioners from both academia and the industry.

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.

Mixed Integer Nonlinear Programming

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Publisher : Springer Science & Business Media
ISBN 13 : 1461419271
Total Pages : 687 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Mixed Integer Nonlinear Programming by : Jon Lee

Download or read book Mixed Integer Nonlinear Programming written by Jon Lee and published by Springer Science & Business Media. This book was released on 2011-12-02 with total page 687 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many engineering, operations, and scientific applications include a mixture of discrete and continuous decision variables and nonlinear relationships involving the decision variables that have a pronounced effect on the set of feasible and optimal solutions. Mixed-integer nonlinear programming (MINLP) problems combine the numerical difficulties of handling nonlinear functions with the challenge of optimizing in the context of nonconvex functions and discrete variables. MINLP is one of the most flexible modeling paradigms available for optimization; but because its scope is so broad, in the most general cases it is hopelessly intractable. Nonetheless, an expanding body of researchers and practitioners — including chemical engineers, operations researchers, industrial engineers, mechanical engineers, economists, statisticians, computer scientists, operations managers, and mathematical programmers — are interested in solving large-scale MINLP instances.

Introduction to Nonlinear Optimization

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Author :
Publisher : SIAM
ISBN 13 : 1611973651
Total Pages : 286 pages
Book Rating : 4.6/5 (119 download)

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Book Synopsis Introduction to Nonlinear Optimization by : Amir Beck

Download or read book Introduction to Nonlinear Optimization written by Amir Beck and published by SIAM. This book was released on 2014-10-27 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the foundations of the theory of nonlinear optimization as well as some related algorithms and presents a variety of applications from diverse areas of applied sciences. The author combines three pillars of optimization?theoretical and algorithmic foundation, familiarity with various applications, and the ability to apply the theory and algorithms on actual problems?and rigorously and gradually builds the connection between theory, algorithms, applications, and implementation. Readers will find more than 170 theoretical, algorithmic, and numerical exercises that deepen and enhance the reader's understanding of the topics. The author includes offers several subjects not typically found in optimization books?for example, optimality conditions in sparsity-constrained optimization, hidden convexity, and total least squares. The book also offers a large number of applications discussed theoretically and algorithmically, such as circle fitting, Chebyshev center, the Fermat?Weber problem, denoising, clustering, total least squares, and orthogonal regression and theoretical and algorithmic topics demonstrated by the MATLAB? toolbox CVX and a package of m-files that is posted on the book?s web site.

Integration of High Voltage AC/DC Grids into Modern Power Systems

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Author :
Publisher : MDPI
ISBN 13 : 3039365258
Total Pages : 140 pages
Book Rating : 4.0/5 (393 download)

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Book Synopsis Integration of High Voltage AC/DC Grids into Modern Power Systems by : Fazel Mohammadi

Download or read book Integration of High Voltage AC/DC Grids into Modern Power Systems written by Fazel Mohammadi and published by MDPI. This book was released on 2020-12-10 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: Electric power transmission relies on AC and DC grids. The extensive integration of conventional and nonconventional energy sources and power converters into power grids has resulted in a demand for high voltage (HV), extra-high voltage (EHV), and ultra-high voltage (UHV) AC/DC transmission grids in modern power systems. To ensure the security, adequacy, and reliable operation of power systems, the practical aspects of interconnecting HV, EHV, and UHV AC/DC grids into the electric power systems, along with their economic and environmental impacts, should be considered. The stability analysis for the planning and operation of HV, EHV, and UHV AC/DC grids in power systems is regarded as another key issue in modern power systems. Moreover, interactions between power converters and other power electronics devices (e.g., FACTS devices) installed on the network are other aspects of power systems that must be addressed. This Special Issue aims to investigate the integration of HV, EHV, and UHV AC/DC grids into modern power systems by analyzing their control, operation, protection, dynamics, planning, reliability, and security, along with considering power quality improvement, market operations, power conversion, cybersecurity, supervisory and monitoring, diagnostics, and prognostics systems.