Global optimization of bilinear programs with a multiparametric disaggregation technique

In this paper, we present the derivation of the multiparametric disaggregation technique (MDT) by Teles et al. (J. Glob. Optim., 2011) for solving nonconvex bilinear programs. Both upper and lower bounding formulations corresponding to mixed-integer linear programs are derived using disjunctive prog...

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Detalhes bibliográficos
Autor principal: Kolodziej, Scott (author)
Outros Autores: Castro, Pedro (author), Grossmann, Ignacio E. (author)
Formato: article
Idioma:eng
Publicado em: 2014
Assuntos:
Texto completo:http://hdl.handle.net/10400.9/2445
País:Portugal
Oai:oai:repositorio.lneg.pt:10400.9/2445
Descrição
Resumo:In this paper, we present the derivation of the multiparametric disaggregation technique (MDT) by Teles et al. (J. Glob. Optim., 2011) for solving nonconvex bilinear programs. Both upper and lower bounding formulations corresponding to mixed-integer linear programs are derived using disjunctive programming and exact linearizations, and incorporated into two global optimization algorithms that are used to solve bilinear programming problems. The relaxation derived using the MDT is shown to scalemuchmore favorably than the relaxation that relies on piecewise McCormick envelopes, yielding smallermixed-integer problems and faster solution times for similar optimality gaps. The proposed relaxation also compares well with general global optimization solvers on large problems.