Enhancing the normalized multiparametric disaggregation technique for mixed-integer quadratic programming

Tiago Andrade, Fabricio Oliveira, Silvio Hamacher, Andrew Eberhard*

*Tämän työn vastaava kirjoittaja

Tutkimustuotos: LehtiartikkeliArticleScientificvertaisarvioitu

20 Sitaatiot (Scopus)
96 Lataukset (Pure)

Abstrakti

We propose methods for improving the relaxations obtained by the normalized multiparametric disaggregation technique (NMDT). These relaxations constitute a key component for some methods for solving nonconvex mixed-integer quadratically constrained quadratic programming (MIQCQP) problems. It is shown that these relaxations can be more efficiently formulated by significantly reducing the number of auxiliary variables (in particular, binary variables) and constraints. Moreover, a novel algorithm for solving MIQCQP problems is proposed. It can be applied using either its original NMDT or the proposed reformulation. Computational experiments are performed using both benchmark instances from the literature and randomly generated instances. The numerical results suggest that the proposed techniques can improve the quality of the relaxations.

AlkuperäiskieliEnglanti
Sivut701–722
JulkaisuJournal of Global Optimization
Vuosikerta73
Numero4
DOI - pysyväislinkit
TilaJulkaistu - huhtik. 2019
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

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