The GOP Approach : Distributed Implementation

  • Christodoulos A. Floudas
Part of the Nonconvex Optimization and Its Applications book series (NOIA, volume 37)

Abstract

In this chapter, we discuss the parallel implementation of the GOP algorithm, as studied by Androulakis et al. (1996), and we present distributed computing results for indefinite quadratic programming problems and for large-scale pooling problems that arise in chemical refineries. Section 7.1 focuses on the critical components of the distributed implementation of the GOP approach. Section 7.2 presents the computational results for large-scale indefinite quadratic problems. Finally, section 7.3 discusses the computational performance of the parallel GOP approach for large-scale blending and pooling problems.

Keywords

Dual Problem Linear Constraint Variable Bound Linear Variable Nonlinear Variable 
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 2000

Authors and Affiliations

  • Christodoulos A. Floudas
    • 1
  1. 1.Department of Chemical EngineeringPrinceton UniversityPrincetonUSA

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