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 77 articles , 2 standard articles )

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  1. Castro, Pedro M.: Spatial branch-and-bound algorithm for MIQCPs featuring multiparametric disaggregation (2017)
  2. Chen, Chen; Atamtürk, Alper; Oren, Shmuel S.: A spatial branch-and-cut method for nonconvex QCQP with bounded complex variables (2017)
  3. Gleixner, Ambros M.; Berthold, Timo; Müller, Benjamin; Weltge, Stefan: Three enhancements for optimization-based bound tightening (2017)
  4. Gupte, Akshay; Ahmed, Shabbir; Dey, Santanu S.; Cheon, Myun Seok: Relaxations and discretizations for the pooling problem (2017)
  5. Newby, Eric; Ali, M. M.: Linear transformation based solution methods for non-convex mixed integer quadratic programs (2017)
  6. Zhao, Yingfeng; Liu, Sanyang: Global optimization algorithm for mixed integer quadratically constrained quadratic program (2017)
  7. Billionnet, Alain; Elloumi, Sourour; Lambert, Amélie: Exact quadratic convex reformulations of mixed-integer quadratically constrained problems (2016)
  8. Birgin, E. G.; Lobato, R. D.; Martínez, J. M.: Packing ellipsoids by nonlinear optimization (2016)
  9. Boland, Natashia; Kalinowski, Thomas; Rigterink, Fabian: New multi-commodity flow formulations for the pooling problem (2016)
  10. Boukouvala, Fani; Misener, Ruth; Floudas, Christodoulos A.: Global optimization advances in mixed-integer nonlinear programming, MINLP, and constrained derivative-free optimization, CDFO (2016)
  11. Castro, Pedro M.: Normalized multiparametric disaggregation: an efficient relaxation for mixed-integer bilinear problems (2016)
  12. Domes, Ferenc; Neumaier, Arnold: Linear and parabolic relaxations for quadratic constraints (2016)
  13. Ma, Xiaohua; Gao, Yuelin; Liu, Xia: A new branch and bound algorithm for integer quadratic programming problems (2016)
  14. Santi, Éverton; Aloise, Daniel; Blanchard, Simon J.: A model for clustering data from heterogeneous dissimilarities (2016)
  15. Aglić Aljinović, A.; Pečarić, J.; Tipurić-Spužević, S.: Weighted quadrature rules via Grüss type inequalities for weighted (L^p) spaces (2015)
  16. 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)
  17. Duan, Qianqian; Yang, Genke; Xu, Guanglin; Duan, Xueyan: A global optimization approach for a class of MINLP problems with applications to crude oil scheduling problem (2015)
  18. Frank, Stephen M.; Rebennack, Steffen: Optimal design of mixed AC-DC distribution systems for commercial buildings: a nonconvex generalized Benders decomposition approach (2015)
  19. Gleixner, Ambros M.: Exact and fast algorithms for mixed-integer nonlinear programming (2015)
  20. Kirst, Peter; Stein, Oliver; Steuermann, Paul: Deterministic upper bounds for spatial branch-and-bound methods in global minimization with nonconvex constraints (2015)

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