SAS® Optimization

Analysts, data scientists and other optimization professionals can identify actions that will produce the best results with this programming entry point, running in SAS® Viya®. By accessing the LP, MILP, network and QP optimization solvers from SAS® clients or from clients other than SAS (Python, Lua, Java and R), you can leverage the speed, scalability and elasticity of the SAS in-memory environment. SAS Optimization requires SAS® Visual Analytics and includes SAS/OR®.

The most recent release is SAS Optimization 8.5.

What’s New

SAS Optimization 8.5 provides improvements to its mathematical optimization procedures, solvers, algorithms, and CAS actions, including the following enhancements:

  • The LP, MILP, and NLP solvers make performance improvements.
  • The MILP solver adds irreducible infeasible set (IIS) analysis.
  • The NLP solver changes its default algorithm and makes three other updates.
  • The runOptmodel action adds support for distributed COFOR loop execution, SUBMIT blocks, and BY-group processing.
  • The LSO solver is renamed the black-box solver.
  • The new solveBlackbox action calls the black-box solver.
  • The cycle detection algorithm adds the ability to output the sequence of links in a cycle.
  • The minimum cut algorithm enables you to specify the pair of nodes the cut must separate.
  • The linear assignment problem algorithm adds a time limit option.

Videos & Tutorials

Ready to build a strong SAS programming foundation? These tutorials are a good place to start.


Find user's guides and other technical documentation for SAS Optimization.

Previous Versions

SAS Technical Papers

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SAS Optimization Blogs & Communities

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