Relaxation And Decomposition Methods For Mixed Integer Nonlinear Programming

Author : Ivo Nowak
Publisher : Springer Science & Business Media
Page : 213 pages
File Size : 49,7 Mb
Release : 2006-03-28
Category : Computers
ISBN : 9783764373740

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Relaxation and Decomposition Methods for Mixed Integer Nonlinear Programming by Ivo Nowak Pdf

Nonlinearoptimizationproblemscontainingbothcontinuousanddiscretevariables are called mixed integer nonlinear programs (MINLP). Such problems arise in many ?elds, such as process industry, engineering design, communications, and ?nance. There is currently a huge gap between MINLP and mixed integer linear programming(MIP) solvertechnology.With a modernstate-of-the-artMIP solver itispossibletosolvemodelswithmillionsofvariablesandconstraints,whereasthe dimensionofsolvableMINLPsisoftenlimitedbyanumberthatissmallerbythree or four orders of magnitude. It is theoretically possible to approximate a general MINLP by a MIP with arbitrary precision. However, good MIP approximations are usually much larger than the original problem. Moreover, the approximation of nonlinear functions by piecewise linear functions can be di?cult and ti- consuming. In this book relaxation and decomposition methods for solving nonconvex structured MINLPs are proposed. In particular, a generic branch-cut-and-price (BCP) framework for MINLP is presented. BCP is the underlying concept in almost all modern MIP solvers. Providing a powerful decomposition framework for both sequential and parallel solvers, it made the success of the current MIP technology possible. So far generic BCP frameworks have been developed only for MIP, for example,COIN/BCP (IBM, 2003) andABACUS (OREAS GmbH, 1999). In order to generalize MIP-BCP to MINLP-BCP, the following points have to be taken into account: • A given (sparse) MINLP is reformulated as a block-separable program with linear coupling constraints.The block structure makes it possible to generate Lagrangian cuts and to apply Lagrangian heuristics. • In order to facilitate the generation of polyhedral relaxations, nonlinear c- vex relaxations are constructed. • The MINLP separation and pricing subproblems for generating cuts and columns are solved with specialized MINLP solvers.

Author : Mohit Tawarmalani,Nikolaos V. Sahinidis
Publisher : Springer Science & Business Media
Page : 492 pages
File Size : 42,5 Mb
Release : 2013-04-17
Category : Mathematics
ISBN : 9781475735321

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Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming by Mohit Tawarmalani,Nikolaos V. Sahinidis Pdf

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.

Author : Jon Lee,Sven Leyffer
Publisher : Springer Science & Business Media
Page : 687 pages
File Size : 55,6 Mb
Release : 2011-12-02
Category : Mathematics
ISBN : 9781461419273

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Mixed Integer Nonlinear Programming by Jon Lee,Sven Leyffer Pdf

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.

Author : Christodoulos A. Floudas
Publisher : Oxford University Press on Demand
Page : 475 pages
File Size : 48,5 Mb
Release : 1995-10-05
Category : Science
ISBN : 9780195100563

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Nonlinear and Mixed-Integer Optimization by Christodoulos A. Floudas Pdf

1. Introduction. PART 1. FUNDAMENTALS OF CONVEX ANALYSIS AND NONLINEAR OPTIMIZATION. 2. Convex Analysis. 3. Fundamentals of Nonlinear Optimization. 4. Duality Theory. PART 2. FUNDAMENTALS OF MIXED-INTEGER OPTIMIZATION. 5. Mixed-Integer Linear Optimization. 6. Mixed-Integer Nonlinear Optimization. PART 3. APPLICATIONS IN PROCESS SYNTHESIS. 7. Process Synthesis. 8. Heat Exchanger Network Synthesis. 9. Distillation-based Separation Systems Synthesis. 10. Synthesis of Reactor Networks and Reactor-Separator-Recycle Systems. Bibliography. Index.

Author : Vladimir Tsurkov
Publisher : Springer Science & Business Media
Page : 322 pages
File Size : 42,7 Mb
Release : 2013-03-09
Category : Computers
ISBN : 9781475732436

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Large-scale Optimization by Vladimir Tsurkov Pdf

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.

Author : Egon Balas
Publisher : Springer
Page : 238 pages
File Size : 55,6 Mb
Release : 2018-11-27
Category : Mathematics
ISBN : 9783030001483

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Disjunctive Programming by Egon Balas Pdf

Disjunctive Programming is a technique and a discipline initiated by the author in the early 1970's, which has become a central tool for solving nonconvex optimization problems like pure or mixed integer programs, through convexification (cutting plane) procedures combined with enumeration. It has played a major role in the revolution in the state of the art of Integer Programming that took place roughly during the period 1990-2010. The main benefit that the reader may acquire from reading this book is a deeper understanding of the theoretical underpinnings and of the applications potential of disjunctive programming, which range from more efficient problem formulation to enhanced modeling capability and improved solution methods for integer and combinatorial optimization. Egon Balas is University Professor and Lord Professor of Operations Research at Carnegie Mellon University's Tepper School of Business.

Author : Antonio J. Conejo,Enrique Castillo,Roberto Minguez,Raquel Garcia-Bertrand
Publisher : Springer Science & Business Media
Page : 542 pages
File Size : 50,8 Mb
Release : 2006-04-28
Category : Technology & Engineering
ISBN : 9783540276869

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Decomposition Techniques in Mathematical Programming by Antonio J. Conejo,Enrique Castillo,Roberto Minguez,Raquel Garcia-Bertrand Pdf

Optimization plainly dominates the design, planning, operation, and c- trol of engineering systems. This is a book on optimization that considers particular cases of optimization problems, those with a decomposable str- ture that can be advantageously exploited. Those decomposable optimization problems are ubiquitous in engineering and science applications. The book considers problems with both complicating constraints and complicating va- ables, and analyzes linear and nonlinear problems, with and without in- ger variables. The decomposition techniques analyzed include Dantzig-Wolfe, Benders, Lagrangian relaxation, Augmented Lagrangian decomposition, and others. Heuristic techniques are also considered. Additionally, a comprehensive sensitivity analysis for characterizing the solution of optimization problems is carried out. This material is particularly novel and of high practical interest. This book is built based on many clarifying, illustrative, and compu- tional examples, which facilitate the learning procedure. For the sake of cl- ity, theoretical concepts and computational algorithms are assembled based on these examples. The results are simplicity, clarity, and easy-learning. We feel that this book is needed by the engineering community that has to tackle complex optimization problems, particularly by practitioners and researchersinEngineering,OperationsResearch,andAppliedEconomics.The descriptions of most decomposition techniques are available only in complex and specialized mathematical journals, di?cult to understand by engineers. A book describing a wide range of decomposition techniques, emphasizing problem-solving, and appropriately blending theory and application, was not previously available.

Author : Duan Li,Xiaoling Sun
Publisher : Springer Science & Business Media
Page : 452 pages
File Size : 45,5 Mb
Release : 2006-08-13
Category : Mathematics
ISBN : 9780387329956

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Nonlinear Integer Programming by Duan Li,Xiaoling Sun Pdf

A combination of both Integer Programming and Nonlinear Optimization, this is a powerful book that surveys the field and provides a state-of-the-art treatment of Nonlinear Integer Programming. It is the first book available on the subject. The book aims to bring the theoretical foundation and solution methods for nonlinear integer programming to students and researchers in optimization, operations research, and computer science.

Author : Ambros Gleixner
Publisher : Unknown
Page : 0 pages
File Size : 46,8 Mb
Release : 2015
Category : Dissertations
ISBN : 383254190X

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Exact and Fast Algorithms for Mixed-integer Nonlinear Programming by Ambros Gleixner Pdf

The discipline of mixed-integer nonlinear programming (MINLP) deals with finite-dimensional optimization problems featuring both discrete choices and nonlinear functions. By this combination, it facilitates more accurate models of real-world systems than possible with purely continuous or purely linear models alone. This book presents new methods that improve the numerical reliability and the computational performance of global MINLP solvers. The author addresses numerical accuracy directly at the linear programming level by means of LP iterative refinement: a new algorithm to solve linear programs to arbitrarily high levels of precision. The computational performance of LP-based MINLP solvers is enhanced by efficient methods to execute and approximate optimization-based bound tightening and by new branching rules that exploit the presence of nonlinear integer variables, i.e., variables both contained in nonlinear terms and required to be integral. The new algorithms help to solve problems which could not be solved before, either due to their numerical complexity or because of limited computing resources.

Author : Christian Kirches
Publisher : Springer Science & Business Media
Page : 380 pages
File Size : 51,9 Mb
Release : 2011-11-23
Category : Computers
ISBN : 9783834882028

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Fast Numerical Methods for Mixed-Integer Nonlinear Model-Predictive Control by Christian Kirches Pdf

Christian Kirches develops a fast numerical algorithm of wide applicability that efficiently solves mixed-integer nonlinear optimal control problems. He uses convexification and relaxation techniques to obtain computationally tractable reformulations for which feasibility and optimality certificates can be given even after discretization and rounding.

Author : A. M. Geoffrion
Publisher : Unknown
Page : 258 pages
File Size : 48,9 Mb
Release : 1972
Category : Mathematics
ISBN : UOM:39015004546514

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Perspectives on Optimization by A. M. Geoffrion Pdf

Author : John K. Karlof
Publisher : CRC Press
Page : 333 pages
File Size : 54,8 Mb
Release : 2005-09-22
Category : Business & Economics
ISBN : 9781420039597

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Integer Programming by John K. Karlof Pdf

Integer Programming: Theory and Practice contains refereed articles that explore both theoretical aspects of integer programming as well as major applications. This volume begins with a description of new constructive and iterative search methods for solving the Boolean optimization problem (BOOP). Following a review of recent developments

Author : Christos T. Maravelias
Publisher : Cambridge University Press
Page : 459 pages
File Size : 50,8 Mb
Release : 2021-05-06
Category : Mathematics
ISBN : 9781107154759

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Chemical Production Scheduling by Christos T. Maravelias Pdf

Understand common scheduling as well as other advanced operational problems with this valuable reference from a recognized leader in the field. Beginning with basic principles and an overview of linear and mixed-integer programming, this unified treatment introduces the fundamental ideas underpinning most modeling approaches, and will allow you to easily develop your own models. With more than 150 figures, the basic concepts and ideas behind the development of different approaches are clearly illustrated. Addresses a wide range of problems arising in diverse industrial sectors, from oil and gas to fine chemicals, and from commodity chemicals to food manufacturing. A perfect resource for engineering and computer science students, researchers working in the area, and industrial practitioners.

Author : Michael Jünger,Thomas M. Liebling,Denis Naddef,George L. Nemhauser,William R. Pulleyblank,Gerhard Reinelt,Giovanni Rinaldi,Laurence A. Wolsey
Publisher : Springer Science & Business Media
Page : 804 pages
File Size : 42,6 Mb
Release : 2009-11-06
Category : Mathematics
ISBN : 9783540682790

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50 Years of Integer Programming 1958-2008 by Michael Jünger,Thomas M. Liebling,Denis Naddef,George L. Nemhauser,William R. Pulleyblank,Gerhard Reinelt,Giovanni Rinaldi,Laurence A. Wolsey Pdf

In 1958, Ralph E. Gomory transformed the field of integer programming when he published a paper that described a cutting-plane algorithm for pure integer programs and announced that the method could be refined to give a finite algorithm for integer programming. In 2008, to commemorate the anniversary of this seminal paper, a special workshop celebrating fifty years of integer programming was held in Aussois, France, as part of the 12th Combinatorial Optimization Workshop. It contains reprints of key historical articles and written versions of survey lectures on six of the hottest topics in the field by distinguished members of the integer programming community. Useful for anyone in mathematics, computer science and operations research, this book exposes mathematical optimization, specifically integer programming and combinatorial optimization, to a broad audience.

Author : Jesús M. Velásquez-Bermúdez,Marzieh Khakifirooz,Mahdi Fathi
Publisher : Springer Nature
Page : 282 pages
File Size : 55,9 Mb
Release : 2019-09-06
Category : Mathematics
ISBN : 9783030227883

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Large Scale Optimization in Supply Chains and Smart Manufacturing by Jesús M. Velásquez-Bermúdez,Marzieh Khakifirooz,Mahdi Fathi Pdf

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.