An improved piecewise outer-approximation algorithm for the global optimization of MINLP models involving concave and bilinear terms

In this paper a new version of the Outer Approximation for Global Optimization Algorithm by Bergamini et al. [Bergamini, M.L., Aguirre, P., & Grossmann, I.E. (2005a). Logic based outer approximation for global optimization of synthesis of process networks. Computers and Chemical Engineering 29,...

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Published in:Computers & chemical engineering Vol. 32; no. 3; pp. 477 - 493
Main Authors: Bergamini, María Lorena, Grossmann, Ignacio, Scenna, Nicolás, Aguirre, Pío
Format: Journal Article
Language:English
Published: Elsevier Ltd 24.03.2008
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ISSN:0098-1354, 1873-4375
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Abstract In this paper a new version of the Outer Approximation for Global Optimization Algorithm by Bergamini et al. [Bergamini, M.L., Aguirre, P., & Grossmann, I.E. (2005a). Logic based outer approximation for global optimization of synthesis of process networks. Computers and Chemical Engineering 29, 1914] is proposed, in order to speed up the convergence in nonconvex MINLP models that involve bilinear and concave terms. Bounding problems are constructed replacing these nonconvex terms by piecewise linear underestimators. These problems, which correspond to mixed-integer linear programs, are solved to generate approximate solutions with improved objective value. When no further feasible solution can be found, this guarantees that the upper bound cannot be improved in the nonconvex problem, thus providing a termination criterion. The new algorithm is applied to five different synthesis problems in the areas of water networks, heat exchanger networks and distillation sequences. The results show a significant reduction in the computational cost compared with the previous version of the algorithm.
AbstractList In this paper a new version of the Outer Approximation for Global Optimization Algorithm by Bergamini et al. [Bergamini, M.L., Aguirre, P., & Grossmann, I.E. (2005a). Logic based outer approximation for global optimization of synthesis of process networks. Computers and Chemical Engineering 29, 1914] is proposed, in order to speed up the convergence in nonconvex MINLP models that involve bilinear and concave terms. Bounding problems are constructed replacing these nonconvex terms by piecewise linear underestimators. These problems, which correspond to mixed-integer linear programs, are solved to generate approximate solutions with improved objective value. When no further feasible solution can be found, this guarantees that the upper bound cannot be improved in the nonconvex problem, thus providing a termination criterion. The new algorithm is applied to five different synthesis problems in the areas of water networks, heat exchanger networks and distillation sequences. The results show a significant reduction in the computational cost compared with the previous version of the algorithm.
Author Bergamini, María Lorena
Aguirre, Pío
Grossmann, Ignacio
Scenna, Nicolás
Author_xml – sequence: 1
  givenname: María Lorena
  surname: Bergamini
  fullname: Bergamini, María Lorena
  organization: Instituto de Desarrollo y Diseño, INGAR, Santa Fe, Argentina
– sequence: 2
  givenname: Ignacio
  surname: Grossmann
  fullname: Grossmann, Ignacio
  organization: Department of Chemical Engineering, Carnegie Mellon University, Pittsburg 15213, USA
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  givenname: Nicolás
  surname: Scenna
  fullname: Scenna, Nicolás
  organization: Instituto de Desarrollo y Diseño, INGAR, Santa Fe, Argentina
– sequence: 4
  givenname: Pío
  surname: Aguirre
  fullname: Aguirre, Pío
  email: paguir@ceride.gov.ar
  organization: Instituto de Desarrollo y Diseño, INGAR, Santa Fe, Argentina
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Keywords MINLP
Piecewise relaxation
Global optimization
Bilinear terms
Concave terms
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Snippet In this paper a new version of the Outer Approximation for Global Optimization Algorithm by Bergamini et al. [Bergamini, M.L., Aguirre, P., & Grossmann, I.E....
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StartPage 477
SubjectTerms Bilinear terms
Concave terms
Global optimization
MINLP
Piecewise relaxation
Title An improved piecewise outer-approximation algorithm for the global optimization of MINLP models involving concave and bilinear terms
URI https://dx.doi.org/10.1016/j.compchemeng.2007.03.011
Volume 32
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