期刊
JOURNAL OF GLOBAL OPTIMIZATION
卷 57, 期 1, 页码 3-50出版社
SPRINGER
DOI: 10.1007/s10898-012-9874-7
关键词
Mixed-integer quadratically-constrained quadratic programs; Numerical optimization software; Mathematical programming reformulations; Branch-and-bound global optimization
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
This paper introduces the global mixed-integer quadratic optimizer, GloMIQO, a numerical solver addressing mixed-integer quadratically-constrained quadratic programs to -global optimality. The algorithmic components are presented for: reformulating user input, detecting special structure including convexity and edge-concavity, generating tight convex relaxations, partitioning the search space, bounding the variables, and finding good feasible solutions. To demonstrate the capacity of GloMIQO, we extensively tested its performance on a test suite of 399 problems of diverse size and structure. The test cases are taken from process networks applications, computational geometry problems, GLOBALLib, MINLPLib, and the Bonmin test set. We compare the performance of GloMIQO with respect to four state-of-the-art global optimization solvers: BARON 10.1.2, Couenne 0.4, LindoGLOBAL 6.1.1.588, and SCIP 2.1.0.
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