Alternative Bounding Approximations for the Global Optimization of Various Engineering Design Problems

  • I. Quesada
  • I. E. Grossmann
Part of the Nonconvex Optimization and Its Applications book series (NOIA, volume 9)


This paper presents a general overview of the global optimization algorithm by Quesada and Grossmann [6] for solving NLP problems involving linear fractional and bilinear terms, and it explores the use of alternative bounding approximations. These are applied in the global optimization of problems arising in different engineering areas and for which different relaxations are proposed depending on the mathematical structure of the models. These relaxations include linear and nonlinear underestimator problems. Reformulations that generate additional estimator functions are also employed. Examples from structural design, batch processes, portfolio investment and layout design are presented.


Feasible Region Layout Design Truss Structure Global Optimization Algorithm Convex Envelope 
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 1996

Authors and Affiliations

  • I. Quesada
    • 1
  • I. E. Grossmann
    • 1
  1. 1.Department of Chemical EngineeringCarnegie Mellon UniversityPittsburghUSA

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