Computational Aspects of Two-segment Separable Programming

Computational Aspects of Two-segment Separable Programming PDF Author: R. R. Meyer
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ISBN:
Category :
Languages : en
Pages :

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Computational Aspects of Two-segment Separable Programming

Computational Aspects of Two-segment Separable Programming PDF Author: R. R. Meyer
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Separable Programming

Separable Programming PDF Author: S.M. Stefanov
Publisher: Springer Science & Business Media
ISBN: 1475734174
Category : Mathematics
Languages : en
Pages : 323

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Book Description
In this book, the author considers separable programming and, in particular, one of its important cases - convex separable programming. Some general results are presented, techniques of approximating the separable problem by linear programming and dynamic programming are considered. Convex separable programs subject to inequality/ equality constraint(s) and bounds on variables are also studied and iterative algorithms of polynomial complexity are proposed. As an application, these algorithms are used in the implementation of stochastic quasigradient methods to some separable stochastic programs. Numerical approximation with respect to I1 and I4 norms, as a convex separable nonsmooth unconstrained minimization problem, is considered as well. Audience: Advanced undergraduate and graduate students, mathematical programming/ operations research specialists.

Separable Optimization

Separable Optimization PDF Author: Stefan M. Stefanov
Publisher: Springer Nature
ISBN: 3030784010
Category : Mathematics
Languages : en
Pages : 360

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Book Description
In this book, the theory, methods and applications of separable optimization are considered. Some general results are presented, techniques of approximating the separable problem by linear programming problem, and dynamic programming are also studied. Convex separable programs subject to inequality/ equality constraint(s) and bounds on variables are also studied and convergent iterative algorithms of polynomial complexity are proposed. As an application, these algorithms are used in the implementation of stochastic quasigradient methods to some separable stochastic programs. The problems of numerical approximation of tabulated functions and numerical solution of overdetermined systems of linear algebraic equations and some systems of nonlinear equations are solved by separable convex unconstrained minimization problems. Some properties of the Knapsack polytope are also studied. This second edition includes a substantial amount of new and revised content. Three new chapters, 15-17, are included. Chapters 15-16 are devoted to the further analysis of the Knapsack problem. Chapter 17 is focused on the analysis of a nonlinear transportation problem. Three new Appendices (E-G) are also added to this edition and present technical details that help round out the coverage. Optimization problems and methods for solving the problems considered are interesting not only from the viewpoint of optimization theory, optimization methods and their applications, but also from the viewpoint of other fields of science, especially the artificial intelligence and machine learning fields within computer science. This book is intended for the researcher, practitioner, or engineer who is interested in the detailed treatment of separable programming and wants to take advantage of the latest theoretical and algorithmic results. It may also be used as a textbook for a special topics course or as a supplementary textbook for graduate courses on nonlinear and convex optimization.

Computational Mathematical Programming

Computational Mathematical Programming PDF Author: Klaus Schittkowski
Publisher: Springer Science & Business Media
ISBN: 3642824501
Category : Mathematics
Languages : en
Pages : 455

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Book Description
This book contains the written versions of main lectures presented at the Advanced Study Institute (ASI) on Computational Mathematical Programming, which was held in Bad Windsheim, Germany F. R., from July 23 to August 2, 1984, under the sponsorship of NATO. The ASI was organized by the Committee on Algorithms (COAL) of the Mathematical Programming Society. Co-directors were Karla Hoffmann (National Bureau of Standards, Washington, U.S.A.) and Jan Teigen (Rabobank Nederland, Zeist, The Netherlands). Ninety participants coming from about 20 different countries attended the ASI and contributed their efforts to achieve a highly interesting and stimulating meeting. Since 1947 when the first linear programming technique was developed, the importance of optimization models and their mathematical solution methods has steadily increased, and now plays a leading role in applied research areas. The basic idea of optimization theory is to minimize (or maximize) a function of several variables subject to certain restrictions. This general mathematical concept covers a broad class of possible practical applications arising in mechanical, electrical, or chemical engineering, physics, economics, medicine, biology, etc. There are both industrial applications (e.g. design of mechanical structures, production plans) and applications in the natural, engineering, and social sciences (e.g. chemical equilibrium problems, christollography problems).

Evaluating Mathematical Programming Techniques

Evaluating Mathematical Programming Techniques PDF Author: J. M. Mulvey
Publisher: Springer Science & Business Media
ISBN: 3642954065
Category : Business & Economics
Languages : en
Pages : 393

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Introduction to Sensitivity and Stability Analysis in Nonlinear Programming

Introduction to Sensitivity and Stability Analysis in Nonlinear Programming PDF Author: Fiacco
Publisher: Academic Press
ISBN: 0080956718
Category : Computers
Languages : en
Pages : 381

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Book Description
Introduction to Sensitivity and Stability Analysis in Nonlinear Programming

Global Optimization

Global Optimization PDF Author: Reiner Horst
Publisher: Springer Science & Business Media
ISBN: 3662025981
Category : Business & Economics
Languages : en
Pages : 705

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Book Description
The enormous practical need for solving global optimization problems coupled with a rapidly advancing computer technology has allowed one to consider problems which a few years ago would have been considered computationally intractable. As a consequence, we are seeing the creation of a large and increasing number of diverse algorithms for solving a wide variety of multiextremal global optimization problems. The goal of this book is to systematically clarify and unify these diverse approaches in order to provide insight into the underlying concepts and their pro perties. Aside from a coherent view of the field much new material is presented. By definition, a multiextremal global optimization problem seeks at least one global minimizer of a real-valued objective function that possesses different local n minimizers. The feasible set of points in IR is usually determined by a system of inequalities. It is well known that in practically all disciplines where mathematical models are used there are many real-world problems which can be formulated as multi extremal global optimization problems.

Spatial Price Equilibrium: Advances in Theory, Computation and Application

Spatial Price Equilibrium: Advances in Theory, Computation and Application PDF Author: Patrick T. Harker
Publisher: Springer Science & Business Media
ISBN: 364246548X
Category : Business & Economics
Languages : en
Pages : 288

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Book Description
The problem of predicting interregional commodity movements and the regional prices of these commodities has intrigued economists, geographers and operations researchers for years. In 1838, A. A. Cournot (1838) discussed the equilibrium of trade between New York and Paris and noted how the equilibrium prices depended upon the transport costs. Enke (1951) recognized that this problem of predicting interregional flows and regional prices could be formulated as a network problem, and in 1952, . Paul Samuelson (1952) used the then recent advances in mathe matical programming to formalize the spatial price equilibrium problem as a nonlinear optimization problem. From this formula tion, Takayama and Judge (1964) derived their quadratic program ming representation of the spatial price equilibrium problem, which they and other scholars then applied to a wide variety of problem contexts. Since these early beginnings, the spatial price equilibrium problem has been widely studied, extended and applied; the paper by Harker (1985) reviews many of these results. In recent years, there has been a growing interest in this problem, as evidenced by the numerous publications listed in Harker (1985). The reasons for this renewed interest are many. First, new applications of this concept have arisen which challenge the theoretical underpinnings of this model. The spatial price equilibrium concept is founded on the assumption of perfect or pure competition. The applications to energy markets, steel markets, etc. have led scholars to rethink the basic structure of this model.

Integer and Separable Programming Techniques for Large Scale Global Optimization Problems

Integer and Separable Programming Techniques for Large Scale Global Optimization Problems PDF Author: Panayote Miltiades Pardalos
Publisher:
ISBN:
Category :
Languages : en
Pages : 214

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A Two-Segment Approximation Algorithm for Separable Convex Programming with Linear Constraints

A Two-Segment Approximation Algorithm for Separable Convex Programming with Linear Constraints PDF Author: Agha Iqbal Ali
Publisher:
ISBN:
Category : Convex programming
Languages : en
Pages : 22

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Document discusses a new algorithm for the separable convex programming with linear constraints. This is based on the approximation of the objective function by at most two linear pieces in the neighborhood of the current feasible solution. The two segments will be adaptively defined rather than predecided fixed grids. If, furthermore, the objective function is differentiable, and one introduces a non-Archimedean infinitesimal, the algorithm generates a sequence of feasible solutions every cluster point of which is an optimal solution. Computational tests on the problem with up to 196 non-linear variables is presented. (Author).