Written for specialists working in optimization, mathematical programming, or control theory. The general theory of path-following and potential reduction interior point polynomial time methods, interior point methods, interior point methods for linear and quadratic programming, polynomial time methods for nonlinear convex programming, efficient computation methods for control problems and variational inequalities, and acceleration of path-following methods are covered. In this book, the authors describe the first unified theory of polynomial-time interior-point methods. Their approach provides a simple and elegant framework in which all known polynomial-time interior-point methods can be explained and analyzed; this approach yields polynomial-time interior-point methods for a wide variety of problems beyond the traditional linear and quadratic programs.

About the Author:

Yurii Nesterov is Senior Research Associate at the Central Economic and Mathematical Institute, Moscow.

Arkadii Nemirovskii is Leading Research Associate at the Central Economic and Mathematical Institute, Moscow.

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Interior-point Polynomial Algorithms in Convex Programming

Nesterov, Yurii; Nemirovskii, Arkadii

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