期刊
NUMERICAL ALGEBRA CONTROL AND OPTIMIZATION
卷 2, 期 4, 页码 739-748出版社
AMER INST MATHEMATICAL SCIENCES-AIMS
DOI: 10.3934/naco.2012.2.739
关键词
Mixed-integer quadratically constrained programming; mixed-integer programming; branch-and-cut; nonconvex; global optimization; software engineering
资金
- DFG Research Center Matheon Mathematics for key technologies in Berlin
We provide a computational study of the performance of a state-ofthe-art solver for nonconvex mixed-integer quadratically constrained programs (MIQCPs). Since successful general-purpose solvers for large problem classes necessarily comprise a variety of algorithmic techniques, we focus especially on the impact of the individual solver components. The solver SCIP used for the experiments implements a branch-and-cut algorithm based on a linear relaxation to solve MIQCPs to global optimality. Our analysis is based on a set of 86 publicly available test instances.
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