A mixed integer (linear) program (mip) is an optimization problem in which a linear objective function is minimized subject to linear constraints over real- and integervalued variables. For details on mixed integer programming, see, e.g., [69,106]. The miplib is a diverse collection of challenging real-world mip instances from various academic and industrial applications suited for benchmarking and testing of mip solution algorithms.

References in zbMATH (referenced in 254 articles , 1 standard article )

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  1. Berthold, Timo: A computational study of primal heuristics inside an MI(NL)P solver (2018)
  2. Berthold, Timo; Farmer, James; Heinz, Stefan; Perregaard, Michael: Parallelization of the FICO Xpress-Optimizer (2018)
  3. Berthold, Timo; Hendel, Gregor; Koch, Thorsten: From feasibility to improvement to proof: three phases of solving mixed-integer programs (2018)
  4. Chen, Wei-Kun; Chen, Liang; Yang, Mu-Ming; Dai, Yu-Hong: Generalized coefficient strengthening cuts for mixed integer programming (2018)
  5. Delorme, Maxence; Iori, Manuel; Martello, Silvano: BPPLIB: a library for bin packing and cutting stock problems (2018)
  6. Dey, Santanu S.; Iroume, Andres; Molinaro, Marco; Salvagnin, Domenico: Improving the randomization step in feasibility pump (2018)
  7. Gurski, Frank; Rethmann, Jochen: Distributed solving of mixed-integer programs with GLPK and Thrift (2018)
  8. Helm, Werner E.; Justkowiak, Jan-Erik: Extension of Mittelmann’s benchmarks: comparing the solvers of SAS and Gurobi (2018)
  9. Ladisch, Frieder; Schürmann, Achill: Equivalence of lattice orbit polytopes (2018)
  10. Munguía, Lluís-Miquel; Ahmed, Shabbir; Bader, David A.; Nemhauser, George L.; Shao, Yufen: Alternating criteria search: a parallel large neighborhood search algorithm for mixed integer programs (2018)
  11. Rihm, Tom; Baumann, Philipp: Staff assignment with lexicographically ordered acceptance levels (2018)
  12. Shinano, Yuji; Berthold, Timo; Heinz, Stefan: ParaXpress: an experimental extension of the FICO Xpress-Optimizer to solve hard MIPs on supercomputers (2018)
  13. Vigerske, Stefan; Gleixner, Ambros: SCIP: global optimization of mixed-integer nonlinear programs in a branch-and-cut framework (2018)
  14. Vitor, Fabio; Easton, Todd: The double pivot simplex method (2018)
  15. Zhou, Kai; Kılınç, Mustafa R.; Chen, Xi; Sahinidis, Nikolaos V.: An efficient strategy for the activation of MIP relaxations in a multicore global MINLP solver (2018)
  16. Alvarez, Alejandro Marcos; Louveaux, Quentin; Wehenkel, Louis: A machine learning-based approximation of strong branching (2017)
  17. Andrea Callia D’Iddio, Michael Huth: Manyopt: An Extensible Tool for Mixed, Non-Linear Optimization Through SMT Solving (2017) arXiv
  18. Arts, Joachim: A multi-item approach to repairable stocking and expediting in a fluctuating demand environment (2017)
  19. Assarf, Benjamin; Gawrilow, Ewgenij; Herr, Katrin; Joswig, Michael; Lorenz, Benjamin; Paffenholz, Andreas; Rehn, Thomas: Computing convex hulls and counting integer points with polymake (2017)
  20. Bajgiran, Omid Sanei; Cire, Andre A.; Rousseau, Louis-Martin: A first look at picking dual variables for maximizing reduced cost fixing (2017)

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Further publications can be found at: http://miplib.zib.de/biblio.html