9783764372385 - Relaxation and Decomposition Methods for Mixed Integer Nonlinear Programming (International Series of Numerical Mathematics, 152, Band 152) von Nowak, Ivo (3 Ergebnisse)

Hardcover. Zustand: Brand New. 1st edition. 213 pages. 9.25x6.50x0.75 inches. In Stock.

Zustand: New. Presents a comprehensive description of theory, algorithms and software for solving nonconvex mixed integer nonlinear programs (MINLP). This book focuses on deterministic global optimization methods, which play a very important role in integer linear programming. It describes basic optimization tools and algorithms. Series: International Series of Numerical Mathematics. Num Pages: 229 pages, 29 black & white tables, biography. BIC Classification: PB. Category: (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 234 x 156 x 14. Weight in Grams: 504. . 2005. Hardback. . . . . Books ship from the US and Ireland.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Nonlinearoptimizationproblemscontainingbothcontinuousanddiscretevar iables 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.