Quadratic Programming Problems

  • Christodoulos A. Floudas
  • Pãnos M. Pardalos
  • Claire S. Adjiman
  • William R. Esposito
  • Zeynep H. Gümüş
  • Stephen T. Harding
  • John L. Klepeis
  • Clifford A. Meyer
  • Carl A. Schweiger
Part of the Nonconvex Optimization and Its Applications book series (NOIA, volume 33)

Abstract

In this chapter nonconvex quadratic programming test problems are considered. These test problems have a quadratic objective function and linear constraints. Quadratic programming has numerous applications (Pardalos and Rosen (1987), Floudas and Visweswaran (1995)) and plays an important role in many nonlinear programming methods. Recent methods of generating challenging quadratic programming test problems and disjointly constrained bilinear programming test problems can be found in the work of Vicente et al. (1992) and Calamai et al. (1993). Furthermore, a very broad class of difficult combinatorial optimization problems such as integer programming, quadratic assignment, and the maximum clique problem can be formulated as nonconvex quadratic programming problems.

Keywords

Objective Function Nonlinear Equality Test Problem Global Solution Linear Inequality 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 1999

Authors and Affiliations

  • Christodoulos A. Floudas
    • 1
  • Pãnos M. Pardalos
    • 2
  • Claire S. Adjiman
    • 1
  • William R. Esposito
    • 1
  • Zeynep H. Gümüş
    • 1
  • Stephen T. Harding
    • 1
  • John L. Klepeis
    • 1
  • Clifford A. Meyer
    • 1
  • Carl A. Schweiger
    • 1
  1. 1.Department of Chemical EngineeringPrinceton UniversityPrincetonUSA
  2. 2.Department of Industrial and Systems EngineeringUniversity of FloridaUSA

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