期刊
MATHEMATICAL PROGRAMMING
卷 136, 期 1, 页码 155-182出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s10107-012-0555-6
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类别
资金
- National Science Foundation [CBET-0827907]
- NSF [DGE-0646086]
- Div Of Chem, Bioeng, Env, & Transp Sys
- Directorate For Engineering [0827907] Funding Source: National Science Foundation
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 epsilon-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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