Constrained Global Optimization: Algorithms and Applications

  • Editors
  • Panos M. Pardalos
  • J. Ben Rosen
Book

Part of the Lecture Notes in Computer Science book series (LNCS, volume 268)

About this book

Introduction

Global optimization is concerned with the characterization and computation of global minima or maxima of nonlinear functions. Such problems are widespread in mathematical modeling of real world systems for a very broad range of applications. The applications include economies of scale, fixed charges, allocation and location problems, quadratic assignment and a number of other combinatorial optimization problems. More recently it has been shown that certain aspects of VLSI chip design and database problems can be formulated as constrained global optimization problems with a quadratic objective function. Although standard nonlinear programming algorithms will usually obtain a local minimum to the problem , such a local minimum will only be global when certain conditions are satisfied (such as f and K being convex).

Keywords

Finite algorithms character computation database design form function global optimization linear optimization modeling nonlinear optimization online optimization programming

Bibliographic information

  • DOI https://doi.org/10.1007/BFb0000035
  • Copyright Information Springer-Verlag 1987
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-18095-1
  • Online ISBN 978-3-540-47755-6
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book
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