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 40 articles , 2 standard articles )

Showing results 1 to 20 of 40.
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  1. Berthold, Timo: A computational study of primal heuristics inside an MI(NL)P solver (2018)
  2. Berthold, Timo: Improving the performance of MIP and MINLP solvers by integrated heuristics (2017)
  3. 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)
  4. 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)
  5. Boukouvala, Fani; Floudas, Christodoulos A.: ARGONAUT: algorithms for global optimization of constrained grey-box computational problems (2017)
  6. Castro, Pedro M.: Spatial branch-and-bound algorithm for MIQCPs featuring multiparametric disaggregation (2017)
  7. Chen, Chen; Atamtürk, Alper; Oren, Shmuel S.: A spatial branch-and-cut method for nonconvex QCQP with bounded complex variables (2017)
  8. Gleixner, Ambros M.; Berthold, Timo; Müller, Benjamin; Weltge, Stefan: Three enhancements for optimization-based bound tightening (2017)
  9. Gupte, Akshay; Ahmed, Shabbir; Dey, Santanu S.; Cheon, Myun Seok: Relaxations and discretizations for the pooling problem (2017)
  10. Newby, Eric; Ali, M.M.: Linear transformation based solution methods for non-convex mixed integer quadratic programs (2017)
  11. Zhao, Yingfeng; Liu, Sanyang: Global optimization algorithm for mixed integer quadratically constrained quadratic program (2017)
  12. Billionnet, Alain; Elloumi, Sourour; Lambert, Amélie: Exact quadratic convex reformulations of mixed-integer quadratically constrained problems (2016)
  13. Birgin, E.G.; Lobato, R.D.; Martínez, J.M.: Packing ellipsoids by nonlinear optimization (2016)
  14. Boland, Natashia; Kalinowski, Thomas; Rigterink, Fabian: New multi-commodity flow formulations for the pooling problem (2016)
  15. Boukouvala, Fani; Misener, Ruth; Floudas, Christodoulos A.: Global optimization advances in mixed-integer nonlinear programming, MINLP, and constrained derivative-free optimization, CDFO (2016)
  16. Castro, Pedro M.: Normalized multiparametric disaggregation: an efficient relaxation for mixed-integer bilinear problems (2016)
  17. Domes, Ferenc; Neumaier, Arnold: Linear and parabolic relaxations for quadratic constraints (2016)
  18. Ma, Xiaohua; Gao, Yuelin; Liu, Xia: A new branch and bound algorithm for integer quadratic programming problems (2016)
  19. Santi, Éverton; Aloise, Daniel; Blanchard, Simon J.: A model for clustering data from heterogeneous dissimilarities (2016)
  20. Ballerstein, Martin; Kienle, Achim; Kunde, Christian; Michaels, Dennis; Weismantel, Robert: Deterministic global optimization of binary hybrid distillation/melt-crystallization processes based on relaxed MINLP formulations (2015)

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