Global optimization of mixed-integer quadratically-constrained quadratic programs (MIQCQP) through piecewise-linear and edge-concave relaxations

We propose a deterministic global optimization approach, whose novel contributions are rooted in the edge-concave and piecewise-linear underestimators, to address nonconvex mixed-integer quadratically-constrained quadratic programs (MIQCQP) to -global optimality. The facets of low-dimensional ( n ≤...

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Published inMathematical programming Vol. 136; no. 1; pp. 155 - 182
Main Authors Misener, Ruth, Floudas, Christodoulos A.
Format Journal Article Conference Proceeding
LanguageEnglish
Published Berlin/Heidelberg Springer-Verlag 01.12.2012
Springer
Springer Nature B.V
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Summary:We propose a deterministic global optimization approach, whose novel contributions are rooted in the edge-concave and piecewise-linear underestimators, to address nonconvex mixed-integer quadratically-constrained quadratic programs (MIQCQP) to -global optimality. The facets of low-dimensional ( n ≤ 3) edge-concave aggregations dominating the termwise relaxation of MIQCQP are introduced at every node of a branch-and-bound tree. Concave multivariable terms and sparsely distributed bilinear terms that do not participate in connected edge-concave aggregations are addressed through piecewise-linear relaxations. Extensive computational studies are presented for point packing problems, standard and generalized pooling problems, and examples from GLOBALLib (Meeraus, Globallib. http://www.gamsworld.org/global/globallib.htm ).
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ISSN:0025-5610
1436-4646
DOI:10.1007/s10107-012-0555-6