GloMIQO

Globally optimizing mixed-integer quadratically-constrained quadratic programs. Major applications of mixed-integer quadratically-constrained quadratic programs (MIQCQP) include quality blending in process networks, separating objects in computational geometry, and portfolio optimization in finance. Specific instantiations of MIQCQP in process networks optimization problems include: pooling problems, distillation sequences, wastewater treatment and total water systems, hybrid energy systems, heat exchanger networks, reactor-separator-recycle systems, separation systems, data reconciliation, batch processes, crude oil scheduling, and natural gas production. Computational geometry problems formulated as MIQCQP include: point packing, cutting convex shapes from rectangles, maximizing the area of a convex polygon, and chip layout and compaction. Portfolio optimization in financial engineering can also be formulated as MIQCQP


References in zbMATH (referenced in 52 articles , 2 standard articles )

Showing results 1 to 20 of 52.
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  1. Baltean-Lugojan, Radu; Misener, Ruth: Piecewise parametric structure in the pooling problem: from sparse strongly-polynomial solutions to NP-hardness (2018)
  2. Berthold, Timo: A computational study of primal heuristics inside an MI(NL)P solver (2018)
  3. Castillo Castillo, Pedro A.; Castro, Pedro M.; Mahalec, Vladimir: Global optimization of MIQCPs with dynamic piecewise relaxations (2018)
  4. Del Pia, Alberto; Khajavirad, Aida: On decomposability of multilinear sets (2018)
  5. Grimstad, Bjarne: A MIQCP formulation for B-spline constraints (2018)
  6. Hasan, M. M. Faruque: An edge-concave underestimator for the global optimization of twice-differentiable nonconvex problems (2018)
  7. Kılınç, Mustafa R.; Sahinidis, Nikolaos V.: Exploiting integrality in the global optimization of mixed-integer nonlinear programming problems with BARON (2018)
  8. Mertens, Nick; Kunde, Christian; Kienle, Achim; Michaels, Dennis: Monotonic reformulation and bound tightening for global optimization of ideal multi-component distillation columns (2018)
  9. Montanher, Tiago; Neumaier, Arnold; Domes, Ferenc: A computational study of global optimization solvers on two trust region subproblems (2018)
  10. Schweiger, Jonas: Exploiting structure in non-convex quadratic optimization and gas network planning under uncertainty (2018)
  11. Vigerske, Stefan; Gleixner, Ambros: SCIP: global optimization of mixed-integer nonlinear programs in a branch-and-cut framework (2018)
  12. Wang, Akang; Hanselman, Christopher L.; Gounaris, Chrysanthos E.: A customized branch-and-bound approach for irregular shape nesting (2018)
  13. Berthold, Timo: Improving the performance of MIP and MINLP solvers by integrated heuristics (2017)
  14. Boland, Natashia; Dey, Santanu S.; Kalinowski, Thomas; Molinaro, Marco; Rigterink, Fabian: Bounding the gap between the McCormick relaxation and the convex hull for bilinear functions (2017)
  15. Boukouvala, Fani; Faruque Hasan, M. M.; Floudas, Christodoulos A.: Global optimization of general constrained grey-box models: new method and its application to constrained PDEs for pressure swing adsorption (2017)
  16. Boukouvala, Fani; Floudas, Christodoulos A.: ARGONAUT: algorithms for global optimization of constrained grey-box computational problems (2017)
  17. Castro, Pedro M.: Spatial branch-and-bound algorithm for MIQCPs featuring multiparametric disaggregation (2017)
  18. Chen, Chen; Atamtürk, Alper; Oren, Shmuel S.: A spatial branch-and-cut method for nonconvex QCQP with bounded complex variables (2017)
  19. Gleixner, Ambros M.; Berthold, Timo; Müller, Benjamin; Weltge, Stefan: Three enhancements for optimization-based bound tightening (2017)
  20. Gupte, Akshay; Ahmed, Shabbir; Dey, Santanu S.; Cheon, Myun Seok: Relaxations and discretizations for the pooling problem (2017)

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Further publications can be found at: http://helios.princeton.edu/GloMIQO/publications.html