Global Optimization With Non Convex Constraints

Download Global Optimization With Non Convex Constraints full books in PDF, epub, and Kindle. Read online Global Optimization With Non Convex Constraints ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Global Optimization with Non-Convex Constraints

Author : Roman G. Strongin
Publisher : Springer Science & Business Media
ISBN 13 : 146154677X
Total Pages : 717 pages
Book Rating : 4.4/5 (615 download)

DOWNLOAD NOW!

Book Synopsis Global Optimization with Non-Convex Constraints by : Roman G. Strongin

Download or read book Global Optimization with Non-Convex Constraints written by Roman G. Strongin and published by Springer Science & Business Media. This book was released on 2013-11-09 with total page 717 pages. Available in PDF, EPUB and Kindle. Book excerpt: Everything should be made as simple as possible, but not simpler. (Albert Einstein, Readers Digest, 1977) The modern practice of creating technical systems and technological processes of high effi.ciency besides the employment of new principles, new materials, new physical effects and other new solutions ( which is very traditional and plays the key role in the selection of the general structure of the object to be designed) also includes the choice of the best combination for the set of parameters (geometrical sizes, electrical and strength characteristics, etc.) concretizing this general structure, because the Variation of these parameters ( with the structure or linkage being already set defined) can essentially affect the objective performance indexes. The mathematical tools for choosing these best combinations are exactly what is this book about. With the advent of computers and the computer-aided design the pro bations of the selected variants are usually performed not for the real examples ( this may require some very expensive building of sample op tions and of the special installations to test them ), but by the analysis of the corresponding mathematical models. The sophistication of the mathematical models for the objects to be designed, which is the natu ral consequence of the raising complexity of these objects, greatly com plicates the objective performance analysis. Today, the main (and very often the only) available instrument for such an analysis is computer aided simulation of an object's behavior, based on numerical experiments with its mathematical model.

Introduction to Global Optimization

Author : R. Horst
Publisher : Springer Science & Business Media
ISBN 13 : 9780792367567
Total Pages : 376 pages
Book Rating : 4.3/5 (675 download)

DOWNLOAD NOW!

Book Synopsis Introduction to Global Optimization by : R. Horst

Download or read book Introduction to Global Optimization written by R. Horst and published by Springer Science & Business Media. This book was released on 2000-12-31 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: A textbook for an undergraduate course in mathematical programming for students with a knowledge of elementary real analysis, linear algebra, and classical linear programming (simple techniques). Focuses on the computation and characterization of global optima of nonlinear functions, rather than the locally optimal solutions addressed by most books on optimization. Incorporates the theoretical, algorithmic, and computational advances of the past three decades that help solve globally multi-extreme problems in the mathematical modeling of real world systems. Annotation copyright by Book News, Inc., Portland, OR

Convex Analysis and Global Optimization

Author : Hoang Tuy
Publisher : Springer Science & Business Media
ISBN 13 : 1475728093
Total Pages : 346 pages
Book Rating : 4.4/5 (757 download)

DOWNLOAD NOW!

Book Synopsis Convex Analysis and Global Optimization by : Hoang Tuy

Download or read book Convex Analysis and Global Optimization written by Hoang Tuy and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the general complementary convex structure underlying most nonconvex optimization problems encountered in applications, convex analysis plays an essential role in the development of global optimization methods. This book develops a coherent and rigorous theory of deterministic global optimization from this point of view. Part I constitutes an introduction to convex analysis, with an emphasis on concepts, properties and results particularly needed for global optimization, including those pertaining to the complementary convex structure. Part II presents the foundation and application of global search principles such as partitioning and cutting, outer and inner approximation, and decomposition to general global optimization problems and to problems with a low-rank nonconvex structure as well as quadratic problems. Much new material is offered, aside from a rigorous mathematical development. Audience: The book is written as a text for graduate students in engineering, mathematics, operations research, computer science and other disciplines dealing with optimization theory. It is also addressed to all scientists in various fields who are interested in mathematical optimization.

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

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

DOWNLOAD NOW!

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.

Frontiers in Global Optimization

Author : Christodoulos A. Floudas
Publisher : Springer Science & Business Media
ISBN 13 : 146130251X
Total Pages : 590 pages
Book Rating : 4.4/5 (613 download)

DOWNLOAD NOW!

Book Synopsis Frontiers in Global Optimization by : Christodoulos A. Floudas

Download or read book Frontiers in Global Optimization written by Christodoulos A. Floudas and published by Springer Science & Business Media. This book was released on 2013-12-01 with total page 590 pages. Available in PDF, EPUB and Kindle. Book excerpt: Global Optimization has emerged as one of the most exciting new areas of mathematical programming. Global optimization has received a wide attraction from many fields in the past few years, due to the success of new algorithms for addressing previously intractable problems from diverse areas such as computational chemistry and biology, biomedicine, structural optimization, computer sciences, operations research, economics, and engineering design and control. This book contains refereed invited papers submitted at the 4th international confer ence on Frontiers in Global Optimization held at Santorini, Greece during June 8-12, 2003. Santorini is one of the few sites of Greece, with wild beauty created by the explosion of a volcano which is in the middle of the gulf of the island. The mystic landscape with its numerous mult-extrema, was an inspiring location particularly for researchers working on global optimization. The three previous conferences on "Recent Advances in Global Opti mization", "State-of-the-Art in Global Optimization", and "Optimization in Computational Chemistry and Molecular Biology: Local and Global approaches" took place at Princeton University in 1991, 1995, and 1999, respectively. The papers in this volume focus on de terministic methods for global optimization, stochastic methods for global optimization, distributed computing methods in global optimization, and applications of global optimiza tion in several branches of applied science and engineering, computer science, computational chemistry, structural biology, and bio-informatics.

Stochastic Adaptive Search for Global Optimization

Author : Z.B. Zabinsky
Publisher : Springer Science & Business Media
ISBN 13 : 9781402075261
Total Pages : 246 pages
Book Rating : 4.0/5 (752 download)

DOWNLOAD NOW!

Book Synopsis Stochastic Adaptive Search for Global Optimization by : Z.B. Zabinsky

Download or read book Stochastic Adaptive Search for Global Optimization written by Z.B. Zabinsky and published by Springer Science & Business Media. This book was released on 2003-09-30 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book overviews several stochastic adaptive search methods for global optimization and provides analytical results regarding their performance and complexity. It develops a class of hit-and-run algorithms that are theoretically motivated and do not require fine-tuning of parameters. Several engineering global optimization problems are summarized to demonstrate the kinds of practical problems that are now within reach. Audience: This book is suitable for graduate students, researchers and practitioners in operations research, engineering, and mathematics.

Convex Analysis and Global Optimization

Author : Hoang Tuy
Publisher : Springer
ISBN 13 : 331931484X
Total Pages : 505 pages
Book Rating : 4.3/5 (193 download)

DOWNLOAD NOW!

Book Synopsis Convex Analysis and Global Optimization by : Hoang Tuy

Download or read book Convex Analysis and Global Optimization written by Hoang Tuy and published by Springer. This book was released on 2016-10-17 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents state-of-the-art results and methodologies in modern global optimization, and has been a staple reference for researchers, engineers, advanced students (also in applied mathematics), and practitioners in various fields of engineering. The second edition has been brought up to date and continues to develop a coherent and rigorous theory of deterministic global optimization, highlighting the essential role of convex analysis. The text has been revised and expanded to meet the needs of research, education, and applications for many years to come. Updates for this new edition include: · Discussion of modern approaches to minimax, fixed point, and equilibrium theorems, and to nonconvex optimization; · Increased focus on dealing more efficiently with ill-posed problems of global optimization, particularly those with hard constraints; · Important discussions of decomposition methods for specially structured problems; · A complete revision of the chapter on nonconvex quadratic programming, in order to encompass the advances made in quadratic optimization since publication of the first edition. · Additionally, this new edition contains entirely new chapters devoted to monotonic optimization, polynomial optimization and optimization under equilibrium constraints, including bilevel programming, multiobjective programming, and optimization with variational inequality constraint. From the reviews of the first edition: The book gives a good review of the topic. ...The text is carefully constructed and well written, the exposition is clear. It leaves a remarkable impression of the concepts, tools and techniques in global optimization. It might also be used as a basis and guideline for lectures on this subject. Students as well as professionals will profitably read and use it.—Mathematical Methods of Operations Research, 49:3 (1999)

Non-Convex Multi-Objective Optimization

Author : Panos M. Pardalos
Publisher : Springer
ISBN 13 : 3319610074
Total Pages : 196 pages
Book Rating : 4.3/5 (196 download)

DOWNLOAD NOW!

Book Synopsis Non-Convex Multi-Objective Optimization by : Panos M. Pardalos

Download or read book Non-Convex Multi-Objective Optimization written by Panos M. Pardalos and published by Springer. This book was released on 2017-07-27 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent results on non-convex multi-objective optimization problems and methods are presented in this book, with particular attention to expensive black-box objective functions. Multi-objective optimization methods facilitate designers, engineers, and researchers to make decisions on appropriate trade-offs between various conflicting goals. A variety of deterministic and stochastic multi-objective optimization methods are developed in this book. Beginning with basic concepts and a review of non-convex single-objective optimization problems; this book moves on to cover multi-objective branch and bound algorithms, worst-case optimal algorithms (for Lipschitz functions and bi-objective problems), statistical models based algorithms, and probabilistic branch and bound approach. Detailed descriptions of new algorithms for non-convex multi-objective optimization, their theoretical substantiation, and examples for practical applications to the cell formation problem in manufacturing engineering, the process design in chemical engineering, and business process management are included to aide researchers and graduate students in mathematics, computer science, engineering, economics, and business management.

Global Optimization in Action

Author : János D. Pintér
Publisher : Springer Science & Business Media
ISBN 13 : 1475725027
Total Pages : 481 pages
Book Rating : 4.4/5 (757 download)

DOWNLOAD NOW!

Book Synopsis Global Optimization in Action by : János D. Pintér

Download or read book Global Optimization in Action written by János D. Pintér and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: In science, engineering and economics, decision problems are frequently modelled by optimizing the value of a (primary) objective function under stated feasibility constraints. In many cases of practical relevance, the optimization problem structure does not warrant the global optimality of local solutions; hence, it is natural to search for the globally best solution(s). Global Optimization in Action provides a comprehensive discussion of adaptive partition strategies to solve global optimization problems under very general structural requirements. A unified approach to numerous known algorithms makes possible straightforward generalizations and extensions, leading to efficient computer-based implementations. A considerable part of the book is devoted to applications, including some generic problems from numerical analysis, and several case studies in environmental systems analysis and management. The book is essentially self-contained and is based on the author's research, in cooperation (on applications) with a number of colleagues. Audience: Professors, students, researchers and other professionals in the fields of operations research, management science, industrial and applied mathematics, computer science, engineering, economics and the environmental sciences.

Global Optimization of Concave Functions Subject to Quadratic Constraints

Author : Faiz Abdullah Al-Khayyal
Publisher :
ISBN 13 :
Total Pages : 24 pages
Book Rating : 4.:/5 (233 download)

DOWNLOAD NOW!

Book Synopsis Global Optimization of Concave Functions Subject to Quadratic Constraints by : Faiz Abdullah Al-Khayyal

Download or read book Global Optimization of Concave Functions Subject to Quadratic Constraints written by Faiz Abdullah Al-Khayyal and published by . This book was released on 1990 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt: For computational purposes, different procedures that accelerate the convergence of the proposed algorithm are analyzed. The second method is based on piecewise linear approximations of the constraint functions. When the constraints are convex the problem is reduced to global concave minimization subject to linear constraints. In the case of non-convex constraints we use zero-one integer variables to linearize the constraints. The number of integer variables depends only on the concave parts of the constraint functions."

Convex Optimization

Author : Stephen P. Boyd
Publisher : Cambridge University Press
ISBN 13 : 9780521833783
Total Pages : 744 pages
Book Rating : 4.8/5 (337 download)

DOWNLOAD NOW!

Book Synopsis Convex Optimization by : Stephen P. Boyd

Download or read book Convex Optimization written by Stephen P. Boyd and published by Cambridge University Press. This book was released on 2004-03-08 with total page 744 pages. Available in PDF, EPUB and Kindle. Book excerpt: Convex optimization problems arise frequently in many different fields. This book provides a comprehensive introduction to the subject, and shows in detail how such problems can be solved numerically with great efficiency. The book begins with the basic elements of convex sets and functions, and then describes various classes of convex optimization problems. Duality and approximation techniques are then covered, as are statistical estimation techniques. Various geometrical problems are then presented, and there is detailed discussion of unconstrained and constrained minimization problems, and interior-point methods. The focus of the book is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. It contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance and economics.

Global Optimization

Author : Leo Liberti
Publisher : Springer Science & Business Media
ISBN 13 : 0387305289
Total Pages : 428 pages
Book Rating : 4.3/5 (873 download)

DOWNLOAD NOW!

Book Synopsis Global Optimization by : Leo Liberti

Download or read book Global Optimization written by Leo Liberti and published by Springer Science & Business Media. This book was released on 2006-06-22 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most global optimization literature focuses on theory. This book, however, contains descriptions of new implementations of general-purpose or problem-specific global optimization algorithms. It discusses existing software packages from which the entire community can learn. The contributors are experts in the discipline of actually getting global optimization to work, and the book provides a source of ideas for people needing to implement global optimization software.

Handbook of Global Optimization

Author : R. Horst
Publisher : Springer Science & Business Media
ISBN 13 : 1461520258
Total Pages : 891 pages
Book Rating : 4.4/5 (615 download)

DOWNLOAD NOW!

Book Synopsis Handbook of Global Optimization by : R. Horst

Download or read book Handbook of Global Optimization written by R. Horst and published by Springer Science & Business Media. This book was released on 2013-12-11 with total page 891 pages. Available in PDF, EPUB and Kindle. Book excerpt: Global optimization is concerned with the computation and characterization of global optima of nonlinear functions. During the past three decades the field of global optimization has been growing at a rapid pace, and the number of publications on all aspects of global optimization has been increasing steadily. Many applications, as well as new theoretical, algorithmic, and computational contributions have resulted. The Handbook of Global Optimization is the first comprehensive book to cover recent developments in global optimization. Each contribution in the Handbook is essentially expository in nature, but scholarly in its treatment. The chapters cover optimality conditions, complexity results, concave minimization, DC programming, general quadratic programming, nonlinear complementarity, minimax problems, multiplicative programming, Lipschitz optimization, fractional programming, network problems, trajectory methods, homotopy methods, interval methods, and stochastic approaches. The Handbook of Global Optimization is addressed to researchers in mathematical programming, as well as all scientists who use optimization methods to model and solve problems.

Frontiers in Global Optimization

Author : Christodoulos A. Floudas
Publisher : Springer Science & Business Media
ISBN 13 : 9781402076992
Total Pages : 612 pages
Book Rating : 4.0/5 (769 download)

DOWNLOAD NOW!

Book Synopsis Frontiers in Global Optimization by : Christodoulos A. Floudas

Download or read book Frontiers in Global Optimization written by Christodoulos A. Floudas and published by Springer Science & Business Media. This book was released on 2004 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt: Global Optimization has emerged as one of the most exciting new areas of mathematical programming. Global optimization has received a wide attraction from many fields in the past few years, due to the success of new algorithms for addressing previously intractable problems from diverse areas such as computational chemistry and biology, biomedicine, structural optimization, computer sciences, operations research, economics, and engineering design and control. The chapters in this volume focus on recent deterministic methods and stochastic methods for global optimization, distributed computing methods in global optimization, and applications of global optimization in several branches of applied science and engineering, computer science, computational chemistry, structural biology, and bio-informatics.

Non-convex Optimization for Machine Learning

Author : Prateek Jain
Publisher : Foundations and Trends in Machine Learning
ISBN 13 : 9781680833683
Total Pages : 218 pages
Book Rating : 4.8/5 (336 download)

DOWNLOAD NOW!

Book Synopsis Non-convex Optimization for Machine Learning by : Prateek Jain

Download or read book Non-convex Optimization for Machine Learning written by Prateek Jain and published by Foundations and Trends in Machine Learning. This book was released on 2017-12-04 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Non-convex Optimization for Machine Learning takes an in-depth look at the basics of non-convex optimization with applications to machine learning. It introduces the rich literature in this area, as well as equips the reader with the tools and techniques needed to apply and analyze simple but powerful procedures for non-convex problems. Non-convex Optimization for Machine Learning is as self-contained as possible while not losing focus of the main topic of non-convex optimization techniques. The monograph initiates the discussion with entire chapters devoted to presenting a tutorial-like treatment of basic concepts in convex analysis and optimization, as well as their non-convex counterparts. The monograph concludes with a look at four interesting applications in the areas of machine learning and signal processing, and exploring how the non-convex optimization techniques introduced earlier can be used to solve these problems. The monograph also contains, for each of the topics discussed, exercises and figures designed to engage the reader, as well as extensive bibliographic notes pointing towards classical works and recent advances. Non-convex Optimization for Machine Learning can be used for a semester-length course on the basics of non-convex optimization with applications to machine learning. On the other hand, it is also possible to cherry pick individual portions, such the chapter on sparse recovery, or the EM algorithm, for inclusion in a broader course. Several courses such as those in machine learning, optimization, and signal processing may benefit from the inclusion of such topics.

Abstract Convexity and Global Optimization

Author : Alexander M. Rubinov
Publisher : Springer Science & Business Media
ISBN 13 : 1475732007
Total Pages : 506 pages
Book Rating : 4.4/5 (757 download)

DOWNLOAD NOW!

Book Synopsis Abstract Convexity and Global Optimization by : Alexander M. Rubinov

Download or read book Abstract Convexity and Global Optimization written by Alexander M. Rubinov and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: Special tools are required for examining and solving optimization problems. The main tools in the study of local optimization are classical calculus and its modern generalizions which form nonsmooth analysis. The gradient and various kinds of generalized derivatives allow us to ac complish a local approximation of a given function in a neighbourhood of a given point. This kind of approximation is very useful in the study of local extrema. However, local approximation alone cannot help to solve many problems of global optimization, so there is a clear need to develop special global tools for solving these problems. The simplest and most well-known area of global and simultaneously local optimization is convex programming. The fundamental tool in the study of convex optimization problems is the subgradient, which actu ally plays both a local and global role. First, a subgradient of a convex function f at a point x carries out a local approximation of f in a neigh bourhood of x. Second, the subgradient permits the construction of an affine function, which does not exceed f over the entire space and coincides with f at x. This affine function h is called a support func tion. Since f(y) ~ h(y) for ally, the second role is global. In contrast to a local approximation, the function h will be called a global affine support.

Handbook of Global Optimization

Author : Panos M. Pardalos
Publisher : Springer Science & Business Media
ISBN 13 : 1475753624
Total Pages : 571 pages
Book Rating : 4.4/5 (757 download)

DOWNLOAD NOW!

Book Synopsis Handbook of Global Optimization by : Panos M. Pardalos

Download or read book Handbook of Global Optimization written by Panos M. Pardalos and published by Springer Science & Business Media. This book was released on 2013-04-18 with total page 571 pages. Available in PDF, EPUB and Kindle. Book excerpt: In 1995 the Handbook of Global Optimization (first volume), edited by R. Horst, and P.M. Pardalos, was published. This second volume of the Handbook of Global Optimization is comprised of chapters dealing with modern approaches to global optimization, including different types of heuristics. Topics covered in the handbook include various metaheuristics, such as simulated annealing, genetic algorithms, neural networks, taboo search, shake-and-bake methods, and deformation methods. In addition, the book contains chapters on new exact stochastic and deterministic approaches to continuous and mixed-integer global optimization, such as stochastic adaptive search, two-phase methods, branch-and-bound methods with new relaxation and branching strategies, algorithms based on local optimization, and dynamical search. Finally, the book contains chapters on experimental analysis of algorithms and software, test problems, and applications.