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 226 articles , 1 standard article )

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  1. Alvarez, Alejandro Marcos; Louveaux, Quentin; Wehenkel, Louis: A machine learning-based approximation of strong branching (2017)
  2. Andrea Callia D’Iddio, Michael Huth: Manyopt: An Extensible Tool for Mixed, Non-Linear Optimization Through SMT Solving (2017) arXiv
  3. Assarf, Benjamin; Gawrilow, Ewgenij; Herr, Katrin; Joswig, Michael; Lorenz, Benjamin; Paffenholz, Andreas; Rehn, Thomas: Computing convex hulls and counting integer points with polymake (2017)
  4. Geißler, Björn; Morsi, Antonio; Schewe, Lars; Schmidt, Martin: Penalty alternating direction methods for mixed-integer optimization: a new view on feasibility pumps (2017)
  5. Gleixner, Ambros M.; Berthold, Timo; Müller, Benjamin; Weltge, Stefan: Three enhancements for optimization-based bound tightening (2017)
  6. Witzig, Jakob; Berthold, Timo; Heinz, Stefan: Experiments with conflict analysis in mixed integer programming (2017)
  7. Belotti, Pietro; Bonami, Pierre; Fischetti, Matteo; Lodi, Andrea; Monaci, Michele; Nogales-Gómez, Amaya; Salvagnin, Domenico: On handling indicator constraints in mixed integer programming (2016)
  8. Berthold, Timo; Farmer, James; Heinz, Stefan; Perregaard, Michael: Parallelization of the FICO Xpress-Optimizer (2016)
  9. Fischetti, Matteo; Lodi, Andrea; Monaci, Michele; Salvagnin, Domenico; Tramontani, Andrea: Improving branch-and-cut performance by random sampling (2016)
  10. Friberg, Henrik A.: CBLIB 2014: a benchmark library for conic mixed-integer and continuous optimization (2016)
  11. Jakob Witzig, Timo Berthold, Stefan Heinz: Experiments with Conflict Analysis in Mixed Integer Programming (2016) arXiv
  12. Kevin K. H. Cheung, Ambros Gleixner, Daniel E. Steffy: Verifying Integer Programming Results (2016) arXiv
  13. Ku, Wen-Yang; Beck, J.Christopher: Mixed integer programming models for job shop scheduling: A computational analysis (2016)
  14. Lalla-Ruiz, Eduardo; Voß, Stefan: Modeling the parallel machine scheduling problem with step deteriorating jobs (2016)
  15. Liberto, Giovanni Di; Kadioglu, Serdar; Leo, Kevin; Malitsky, Yuri: DASH: dynamic approach for switching heuristics (2016)
  16. Rebennack, Steffen: Computing tight bounds via piecewise linear functions through the example of circle cutting problems (2016)
  17. Salvagnin, Domenico: Detecting semantic groups in MIP models (2016)
  18. Santos, Haroldo G.; Toffolo, Túlio A.M.; Gomes, Rafael A.M.; Ribas, Sabir: Integer programming techniques for the nurse rostering problem (2016)
  19. Yuh, Junsang; Lee, Youngho: Surrogate-RLT cuts for zero-one integer programs (2016)
  20. Baena, Daniel; Castro, Jordi; González, José A.: Fix-and-relax approaches for controlled tabular adjustment (2015)

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