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 300 articles , 1 standard article )

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  1. Basso, S.; Ceselli, Alberto; Tettamanzi, Andrea: Random sampling and machine learning to understand good decompositions (2020)
  2. Bastubbe, Michael; Lübbecke, Marco E.: A branch-and-price algorithm for capacitated hypergraph vertex separation (2020)
  3. Fukasawa, Ricardo; Poirrier, Laurent; Yang, Shenghao: Split cuts from sparse disjunctions (2020)
  4. Gleixner, Ambros; Steffy, Daniel E.: Linear programming using limited-precision oracles (2020)
  5. Goerigk, Marc; Maher, Stephen J.: Generating hard instances for robust combinatorial optimization (2020)
  6. Kazachkov, Aleksandr M.; Nadarajah, Selvaprabu; Balas, Egon; Margot, François: Partial hyperplane activation for generalized intersection cuts (2020)
  7. Müller, Benjamin; Serrano, Felipe; Gleixner, Ambros: Using two-dimensional projections for stronger separation and propagation of bilinear terms (2020)
  8. Basu, Amitabh; Sankaranarayanan, Sriram: Can cut-generating functions be good and efficient? (2019)
  9. Braun, Gábor; Pokutta, Sebastian; Zink, Daniel: Lazifying conditional gradient algorithms (2019)
  10. Eilbrecht, Jan; Stursberg, Olaf: Hierarchical solution of non-convex optimal control problems with application to autonomous driving (2019)
  11. Fukasawa, Ricardo; Poirrier, Laurent: Permutations in the factorization of simplex bases (2019)
  12. Fukasawa, Ricardo; Poirrier, Laurent; Xavier, Álinson S.: The (not so) trivial lifting in two dimensions (2019)
  13. Furini, Fabio; Traversi, Emiliano; Belotti, Pietro; Frangioni, Antonio; Gleixner, Ambros; Gould, Nick; Liberti, Leo; Lodi, Andrea; Misener, Ruth; Mittelmann, Hans; Sahinidis, Nikolaos V.; Vigerske, Stefan; Wiegele, Angelika: QPLIB: a library of quadratic programming instances (2019)
  14. Gamrath, Gerald; Berthold, Timo; Heinz, Stefan; Winkler, Michael: Structure-driven fix-and-propagate heuristics for mixed integer programming (2019)
  15. Hojny, Christopher; Pfetsch, Marc E.: Polytopes associated with symmetry handling (2019)
  16. Ilbin, Lee; Stewart, Curry; Nicoleta, Serban: Solving large batches of linear programs (2019)
  17. Munguía, Lluís-Miquel; Ahmed, Shabbir; Bader, David A.; Nemhauser, George L.; Shao, Yufen; Papageorgiou, Dimitri J.: Tailoring parallel alternating criteria search for domain specific MIPs: application to maritime inventory routing (2019)
  18. Neumann, Christoph; Stein, Oliver; Sudermann-Merx, Nathan: A feasible rounding approach for mixed-integer optimization problems (2019)
  19. Pfetsch, Marc E.; Rehn, Thomas: A computational comparison of symmetry handling methods for mixed integer programs (2019)
  20. Schewe, Lars; Schmidt, Martin: Computing feasible points for binary MINLPs with MPECs (2019)

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