Abstrakti
In this paper we describe a method for obtaining sets of transformations for reformulating a mixed integer nonlinear programming (MINLP) problem containing nonconvex twice-differentiable (C-2) functions to a convex MINLP problem in an extended variable space. The method for obtaining the transformations is based on solving a mixed integer linear programming (MILP) problem given the structure of the nonconvex MINLP problem. The solution of the MILP problem renders a minimal set of transformations convexifying the nonconvex problem. This technique is implemented as an part of the alpha signomial global optimization algorithm (alpha SGO), a global optimization algorithm for nonconvex MINLP problems.
Alkuperäiskieli | Ei tiedossa |
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Otsikko | 11th International Symposium on Process Systems Engineering |
Toimittajat | Iftekhar A Karimi, Rajagopalan Srinivasan |
Kustantaja | Elsevier |
Sivut | 1497–1501 |
Sivumäärä | 5 |
ISBN (painettu) | 978-0-444-59505-8 |
Tila | Julkaistu - 2012 |
OKM-julkaisutyyppi | A4 Artikkeli konferenssijulkaisuussa |
Tapahtuma | conference - Kesto: 1 tammik. 2012 → … |
Konferenssi
Konferenssi | conference |
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Ajanjakso | 01/01/12 → … |
Keywords
- global optimization
- nonconvex MINLP problems
- reformulation techniques
- signomial functions