Nonlinear and Mixed-Integer Optimization

Nonlinear and Mixed-Integer Optimization PDF Author: Christodoulos A. Floudas
Publisher: Oxford University Press
ISBN: 0195100565
Category : Business & Economics
Languages : en
Pages : 475

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Book Description
This volume presents the fundamentals of nonlinear and mixed-integer optimisation, and their applications in the important area of process synthesis in chemical engineering. Topics that are unique include the theory and methods for mixed-integer nonlinear optimisation, introduction to modelling issues in process synthesis, and optimisation-based approaches in the synthesis of heat recovery systems, distillation-based systems, and reactor-based systems.

Nonlinear and Mixed-Integer Optimization

Nonlinear and Mixed-Integer Optimization PDF Author: Christodoulos A. Floudas
Publisher: Oxford University Press
ISBN: 0195100565
Category : Business & Economics
Languages : en
Pages : 475

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Book Description
This volume presents the fundamentals of nonlinear and mixed-integer optimisation, and their applications in the important area of process synthesis in chemical engineering. Topics that are unique include the theory and methods for mixed-integer nonlinear optimisation, introduction to modelling issues in process synthesis, and optimisation-based approaches in the synthesis of heat recovery systems, distillation-based systems, and reactor-based systems.

Mixed Integer Nonlinear Programming

Mixed Integer Nonlinear Programming PDF Author: Jon Lee
Publisher: Springer Science & Business Media
ISBN: 1461419271
Category : Mathematics
Languages : en
Pages : 687

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Book Description
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.

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

Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming PDF Author: Mohit Tawarmalani
Publisher: Springer Science & Business Media
ISBN: 1475735324
Category : Mathematics
Languages : en
Pages : 492

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Book Description
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.

Disjunctive Programming

Disjunctive Programming PDF Author: Egon Balas
Publisher: Springer
ISBN: 3030001482
Category : Mathematics
Languages : en
Pages : 238

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Book Description
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.

Handbook of Combinatorial Optimization

Handbook of Combinatorial Optimization PDF Author: Ding-Zhu Du
Publisher: Springer Science & Business Media
ISBN: 0387238301
Category : Business & Economics
Languages : en
Pages : 395

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Book Description
This is a supplementary volume to the major three-volume Handbook of Combinatorial Optimization set. It can also be regarded as a stand-alone volume presenting chapters dealing with various aspects of the subject in a self-contained way.

Fast Numerical Methods for Mixed-Integer Nonlinear Model-Predictive Control

Fast Numerical Methods for Mixed-Integer Nonlinear Model-Predictive Control PDF Author: Christian Kirches
Publisher: Springer Science & Business Media
ISBN: 383488202X
Category : Computers
Languages : en
Pages : 380

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Book Description
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.

Relaxation and Decomposition Methods for Mixed Integer Nonlinear Programming

Relaxation and Decomposition Methods for Mixed Integer Nonlinear Programming PDF Author: Ivo Nowak
Publisher: Springer Science & Business Media
ISBN: 9783764372385
Category : Computers
Languages : en
Pages : 242

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Book Description
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.

Large-Scale Optimization with Applications

Large-Scale Optimization with Applications PDF Author: Lorenz T. Biegler
Publisher: Springer Science & Business Media
ISBN: 1461219620
Category : Mathematics
Languages : en
Pages : 219

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Book Description
With contributions by specialists in optimization and practitioners in the fields of aerospace engineering, chemical engineering, and fluid and solid mechanics, the major themes include an assessment of the state of the art in optimization algorithms as well as challenging applications in design and control, in the areas of process engineering and systems with partial differential equation models.

Nonlinear and Mixed-Integer Optimization

Nonlinear and Mixed-Integer Optimization PDF Author: Christodoulos A. Floudas
Publisher: Oxford University Press
ISBN: 0195356551
Category : Science
Languages : en
Pages : 475

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Book Description
Filling a void in chemical engineering and optimization literature, this book presents the theory and methods for nonlinear and mixed-integer optimization, and their applications in the important area of process synthesis. Other topics include modeling issues in process synthesis, and optimization-based approaches in the synthesis of heat recovery systems, distillation-based systems, and reactor-based systems. The basics of convex analysis and nonlinear optimization are also covered and the elementary concepts of mixed-integer linear optimization are introduced. All chapters have several illustrations and geometrical interpretations of the material as well as suggested problems. Nonlinear and Mixed-Integer Optimization will prove to be an invaluable source--either as a textbook or a reference--for researchers and graduate students interested in continuous and discrete nonlinear optimization issues in engineering design, process synthesis, process operations, applied mathematics, operations research, industrial management, and systems engineering.

Business Optimization Using Mathematical Programming

Business Optimization Using Mathematical Programming PDF Author: Josef Kallrath
Publisher: Springer Nature
ISBN: 3030732371
Category : Business & Economics
Languages : en
Pages : 653

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Book Description
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.