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Global Optimization of Convex Multiplicative Programs by Duality Theory

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Global Optimization and Constraint Satisfaction (COCOS 2003)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3478))

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Abstract

A global optimization approach for convex multiplicative problems based on the generalized Benders decomposition is proposed. A suitable representation of the multiplicative problem in the outcome space reduces its global solution to the solution of a sequence of quasiconcave minimizations over polytopes. Some similarities between convex multiplicative and convex multiobjective programming become evident through the methodology proposed. The algorithm is easily implemented; its performance is illustrated by a test problem.

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Author information

Authors and Affiliations

  1. Faculty of Electrical & Computer Engineering, University of Campinas, 13084-970, Campinas/SP, Brazil

    RĂºbia M. Oliveira & Paulo A. V. Ferreira

Authors
  1. RĂºbia M. Oliveira
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  2. Paulo A. V. Ferreira
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Editor information

Editors and Affiliations

  1. LINA, FRE CNRS 2729 – University of Nantes, 2, rue de la Houssinière, BP 92208, F-44322, Nantes cedex 3, France

    Christophe Jermann

  2. Institute for Mathematics, University Wien, Nordbergstr. 15, A-1090, Wien, Austria

    Arnold Neumaier

  3. Artificial Intelligence Laboratory, Swiss Federal Institute of Technology, Route J.-D. Colladon, Bat. INR, Office 235, CH-1015, Lausanne, Switzerland

    Djamila Sam

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© 2005 Springer-Verlag Berlin Heidelberg

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Oliveira, R.M., Ferreira, P.A.V. (2005). Global Optimization of Convex Multiplicative Programs by Duality Theory. In: Jermann, C., Neumaier, A., Sam, D. (eds) Global Optimization and Constraint Satisfaction. COCOS 2003. Lecture Notes in Computer Science, vol 3478. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11425076_8

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  • DOI: https://doi.org/10.1007/11425076_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26003-5

  • Online ISBN: 978-3-540-32041-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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