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Global Optimization

Deterministic Approaches

  • Book
  • © 1990

Overview

Authors:
  1. Reiner Horst

    1. Department of Mathematics, University of Trier, Trier, Germany

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    You can also search for this author in PubMed   Google Scholar

  2. Hoang Tuy

    1. Institute of Mathematics, Vien Toan Hoc, Hanoi, Vietnam

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    You can also search for this author in PubMed   Google Scholar

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Table of contents (11 chapters)

  1. Front Matter

    Pages I-XIV
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  2. Introduction and Basic Techniques

    1. Front Matter

      Pages 1-1
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    2. Some Important Classes of Global Optimization Problems

      • Reiner Horst, Hoang Tuy
      Pages 3-50

    3. Outer Approximation

      • Reiner Horst, Hoang Tuy
      Pages 51-84

    4. Concavity Cuts

      • Reiner Horst, Hoang Tuy
      Pages 85-110

    5. Branch and Bound

      • Reiner Horst, Hoang Tuy
      Pages 111-172

  3. Concave Minimization

    1. Front Matter

      Pages 173-173
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    2. Cutting Methods

      • Reiner Horst, Hoang Tuy
      Pages 175-218

    3. Successive Approximation Methods

      • Reiner Horst, Hoang Tuy
      Pages 219-285

    4. Successive Partition Methods

      • Reiner Horst, Hoang Tuy
      Pages 286-370

    5. Decomposition of Large Scale Problems

      • Reiner Horst, Hoang Tuy
      Pages 371-433

    6. Special Problems of Concave Minimization

      • Reiner Horst, Hoang Tuy
      Pages 434-501

  4. General Nonlinear Problems

    1. Front Matter

      Pages 503-503
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    2. D.C. Programming

      • Reiner Horst, Hoang Tuy
      Pages 505-586

    3. Lipschitz and Continuous Optimization

      • Reiner Horst, Hoang Tuy
      Pages 587-655

  5. Back Matter

    Pages 657-696
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Keywords

About this book

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.

Authors and Affiliations

  • Department of Mathematics, University of Trier, Trier, Germany

    Reiner Horst

  • Institute of Mathematics, Vien Toan Hoc, Hanoi, Vietnam

    Hoang Tuy

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