MIPLIB

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 284 articles , 1 standard article )

Showing results 1 to 20 of 284.
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  1. Goerigk, Marc; Maher, Stephen J.: Generating hard instances for robust combinatorial optimization (2020)
  2. Basu, Amitabh; Sankaranarayanan, Sriram: Can cut-generating functions be good and efficient? (2019)
  3. Braun, Gábor; Pokutta, Sebastian; Zink, Daniel: Lazifying conditional gradient algorithms (2019)
  4. 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)
  5. Hojny, Christopher; Pfetsch, Marc E.: Polytopes associated with symmetry handling (2019)
  6. 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)
  7. Neumann, Christoph; Stein, Oliver; Sudermann-Merx, Nathan: A feasible rounding approach for mixed-integer optimization problems (2019)
  8. Pfetsch, Marc E.; Rehn, Thomas: A computational comparison of symmetry handling methods for mixed integer programs (2019)
  9. Schewe, Lars; Schmidt, Martin: Computing feasible points for binary MINLPs with MPECs (2019)
  10. Berthold, Timo: A computational study of primal heuristics inside an MI(NL)P solver (2018)
  11. Berthold, Timo; Farmer, James; Heinz, Stefan; Perregaard, Michael: Parallelization of the FICO Xpress-Optimizer (2018)
  12. Berthold, Timo; Hendel, Gregor; Koch, Thorsten: From feasibility to improvement to proof: three phases of solving mixed-integer programs (2018)
  13. Berthold, Timo; Perregaard, Michael; Mészáros, Csaba: Four good reasons to use an interior point solver within a MIP solver (2018)
  14. Chen, Wei-Kun; Chen, Liang; Yang, Mu-Ming; Dai, Yu-Hong: Generalized coefficient strengthening cuts for mixed integer programming (2018)
  15. da Costa Vieira Rezende, Josiane; Souza, Marcone Jamilson Freitas; Coelho, Vitor Nazário; Martins, Alexandre Xavier: HMS: a hybrid multi-start algorithm for solving binary linear programs (2018)
  16. Delorme, Maxence; Iori, Manuel; Martello, Silvano: BPPLIB: a library for bin packing and cutting stock problems (2018)
  17. Dey, Santanu S.; Iroume, Andres; Molinaro, Marco; Salvagnin, Domenico: Improving the randomization step in feasibility pump (2018)
  18. Dey, Santanu S.; Molinaro, Marco: Theoretical challenges towards cutting-plane selection (2018)
  19. Fischetti, Matteo; Ljubić, Ivana; Monaci, Michele; Sinnl, Markus: On the use of intersection cuts for bilevel optimization (2018)
  20. Fischetti, Matteo; Monaci, Michele; Salvagnin, Domenico: SelfSplit parallelization for mixed-integer linear programming (2018)

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