Author: Yinyu YePublisher:
ISBN:
Category :
Languages : en
Pages : 34
Book Description
Containing and Shrinking Ellipsoids in the Path-following Algorithm
Author: Yinyu YeHandbook of Convex Geometry
Author: Bozzano G LuisaPublisher: Elsevier
ISBN: 0080934390
Category : Mathematics
Languages : en
Pages : 803
Book Description
Handbook of Convex Geometry, Volume A offers a survey of convex geometry and its many ramifications and relations with other areas of mathematics, including convexity, geometric inequalities, and convex sets. The selection first offers information on the history of convexity, characterizations of convex sets, and mixed volumes. Topics include elementary convexity, equality in the Aleksandrov-Fenchel inequality, mixed surface area measures, characteristic properties of convex sets in analysis and differential geometry, and extensions of the notion of a convex set. The text then reviews the standard isoperimetric theorem and stability of geometric inequalities. The manuscript takes a look at selected affine isoperimetric inequalities, extremum problems for convex discs and polyhedra, and rigidity. Discussions focus on include infinitesimal and static rigidity related to surfaces, isoperimetric problem for convex polyhedral, bounds for the volume of a convex polyhedron, curvature image inequality, Busemann intersection inequality and its relatives, and Petty projection inequality. The book then tackles geometric algorithms, convexity and discrete optimization, mathematical programming and convex geometry, and the combinatorial aspects of convex polytopes. The selection is a valuable source of data for mathematicians and researchers interested in convex geometry.
Optimization
Author: Szymon DoleckiPublisher: Springer
ISBN: 3540468676
Category : Mathematics
Languages : en
Pages : 227
Book Description
The 2-yearly French-German Conferences on Optimization review the state-of-the-art and the trends in the field. The proceedings of the Fifth Conference include papers on projective methods in linear programming (special session at the conference), nonsmooth optimization, two-level optimization, multiobjective optimization, partial inverse method, variational convergence, Newton type algorithms and flows and on practical applications of optimization. A. Ioffe and J.-Ph. Vial have contributed survey papers on, respectively second order optimality conditions and projective methods in linear programming.
Linear Programming and Network Flows
Author: Mokhtar S. BazaraaPublisher: John Wiley & Sons
ISBN: 0471703761
Category : Mathematics
Languages : en
Pages : 764
Book Description
Linear Programming and Network Flows, now in its third edition, addresses the problem of minimizing or maximizing a linear function in the presence of linear equality or inequility constraints. This book: * Provides methods for modeling complex problems via effective algorithms on modern computers. * Presents the general theory and characteristics of optimization problems, along with effective solution algorithms. * Explores linear programming (LP) and network flows, employing polynomial-time algorithms and various specializations of the simplex method.
Linear Programming: Mathematics, Theory and Algorithms
Author: M.J. PanikPublisher: Springer Science & Business Media
ISBN: 1461334349
Category : Mathematics
Languages : en
Pages : 502
Book Description
Linear Programming provides an in-depth look at simplex based as well as the more recent interior point techniques for solving linear programming problems. Starting with a review of the mathematical underpinnings of these approaches, the text provides details of the primal and dual simplex methods with the primal-dual, composite, and steepest edge simplex algorithms. This then is followed by a discussion of interior point techniques, including projective and affine potential reduction, primal and dual affine scaling, and path following algorithms. Also covered is the theory and solution of the linear complementarity problem using both the complementary pivot algorithm and interior point routines. A feature of the book is its early and extensive development and use of duality theory. Audience: The book is written for students in the areas of mathematics, economics, engineering and management science, and professionals who need a sound foundation in the important and dynamic discipline of linear programming.
Optimization Theory and Methods
Author: Wenyu SunPublisher: Springer Science & Business Media
ISBN: 0387249761
Category : Mathematics
Languages : en
Pages : 689
Book Description
Optimization Theory and Methods can be used as a textbook for an optimization course for graduates and senior undergraduates. It is the result of the author's teaching and research over the past decade. It describes optimization theory and several powerful methods. For most methods, the book discusses an idea’s motivation, studies the derivation, establishes the global and local convergence, describes algorithmic steps, and discusses the numerical performance.
Mathematical Developments Arising from Linear Programming
Author: Jeffrey C. LagariasPublisher: American Mathematical Soc.
ISBN: 0821851217
Category : Mathematics
Languages : en
Pages : 360
Book Description
There has been much recent work in linear and non-linear programming centred on understanding and extending the ideas underlying Karmarkar's interior-point linear programming algorithm. This volume is the result of an AMS conference on mathematical developments arising from linear programming.
Introduction to Continuous Optimization
Author: Roman A. PolyakPublisher: Springer Nature
ISBN: 3030687139
Category : Mathematics
Languages : en
Pages : 552
Book Description
This self-contained monograph presents the reader with an authoritative view of Continuous Optimization, an area of mathematical optimization that has experienced major developments during the past 40 years. The book contains results which have not yet been covered in a systematic way as well as a summary of results on NR theory and methods developed over the last several decades. The readership is aimed to graduate students in applied mathematics, computer science, economics, as well as researchers working in optimization and those applying optimization methods for solving real life problems. Sufficient exercises throughout provide graduate students and instructors with practical utility in a two-semester course in Continuous Optimization. The topical coverage includes interior point methods, self-concordance theory and related complexity issues, first and second order methods with accelerated convergence, nonlinear rescaling (NR) theory and exterior point methods, just to mention a few. The book contains a unified approach to both interior and exterior point methods with emphasis of the crucial duality role. One of the main achievements of the book shows what makes the exterior point methods numerically attractive and why. The book is composed in five parts. The first part contains the basics of calculus, convex analysis, elements of unconstrained optimization, as well as classical results of linear and convex optimization. The second part contains the basics of self-concordance theory and interior point methods, including complexity results for LP, QP, and QP with quadratic constraint, semidefinite and conic programming. In the third part, the NR and Lagrangian transformation theories are considered and exterior point methods are described. Three important problems in finding equilibrium are considered in the fourth part. In the fifth and final part of the book, several important applications arising in economics, structural optimization, medicine, statistical learning theory, and more, are detailed. Numerical results, obtained by solving a number of real life and test problems, are also provided.
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