SAS/OR

SAS/OR software provides a powerful array of optimization, project scheduling and simulation techniques to identify the actions that will produce the best results, while operating within resource limitations and tight restrictions. It enables organizations to consider more alternative actions and scenarios, and determine the best allocation of resources and the best plans for accomplishing goals.

Keywords for this software

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References in zbMATH (referenced in 7 articles )

Showing results 1 to 7 of 7.
Sorted by year (citations)

  1. Gleixner, Ambros; Hendel, Gregor; Gamrath, Gerald; Achterberg, Tobias; Bastubbe, Michael; Berthold, Timo; Christophel, Philipp; Jarck, Kati; Koch, Thorsten; Linderoth, Jeff; Lübbecke, Marco; Mittelmann, Hans D.; Ozyurt, Derya; Ralphs, Ted K.; Salvagnin, Domenico; Shinano, Yuji: MIPLIB 2017: data-driven compilation of the 6th mixed-integer programming library (2021)
  2. Helm, Werner E.; Justkowiak, Jan-Erik: Extension of Mittelmann’s benchmarks: comparing the solvers of SAS and Gurobi (2018)
  3. Roberto Fontana; Sabrina Sampò: Minimum-Size Mixed-Level Orthogonal Fractional Factorial Designs Generation: A SAS-Based Algorithm (2013) not zbMATH
  4. Rendall, Michael S.; Admiraal, Ryan; DeRose, Alessandra; DiGiulio, Paola; Handcock, Mark S.; Racioppi, Filomena: Population constraints on pooled surveys in demographic hazard modeling (2008)
  5. Emrouznejad, Ali: Measurement efficiency and productivity in SAS/OR (2005)
  6. Garnett McMillan; Timothy Hanson: SAS Macro BDM for Fitting the Dale Regression Model to Bivariate Ordinal Response Data (2005) not zbMATH
  7. Gao, Sujuan: Combining binomial data using the logistic normal model (2004)


Further publications can be found at: http://support.sas.com/resources/papers/index.html