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SAS/OR® Software

Optimize business processes and address management science challenges


Mathematical optimisation
  • The OPTMODEL family of procedures provides:
    • Use of industry-standard MPS/QPS format input data sets.
    • Flexible syntax for intuitive model formulation.
    • Support for the transparent use of standard SAS functions.
    • Direct invocation of linear, nonlinear, quadratic and mixed-integer solvers.
    • Support for the rapid prototyping of customized optimisation algorithms.
  • Aggressive presolvers to reduce effective problem size.
  • Linear programming solvers:
    • Primal simplex and dual simplex.
    • Iterative interior-point.
  • New branch-and-bound integer and mixed-integer programming solver with cutting planes and primal heuristics.
  • Continued support for the original LP (linear and mixed-integer programming) procedure.
  • General nonlinear programming solvers:
    • Unconstrained: LBFGS, Fletcher-Reeves, Polak-Ribiere.
    • Constrained: conjugate gradient, Newton-Raphson, trust region.
    • Nonlinearly constrained: SQP.
  • Quadratic programming with state-of-the-art solver tailored for large-scale optimisation .
  • Network flow optimisation .
  • Genetic algorithms for local search optimisation .

Project and resource scheduling
  • Critical Path Method and CPM-based resource-constrained scheduling.
  • Calendars, work shifts and holidays for determining resource availability and schedules.
  • Full support for nonstandard precedence relationships.
  • Ability to include PERT estimates of duration.
  • Versatile reporting, customizable Gantt charts and project network diagrams.
  • Earned Value Management analysis.
  • Decision analysis:
    • Create, analyze and interactively modify decision tree models.
    • Customize utility functions, including risk aversion/tolerance.
    • Calculate Value of Perfect Information (VPI) and Value of Perfect Control (VPC).
  • Bill of materials (BOM) processing:
    • Reads from standard product structure data files and part master files, or combined file.
    • Accounts for lead times, lead time offsets, scrap factors, quantities on hand.
    • Produces single- or multi-level bills of material, including indented and summarized BOM.
    • Produces summarized parts, listing items and quantities required to meet the specified plan.
  • New constraint programming capabilities*.

Discrete event simulation
  • Versatile, graphical modeling capabilities; create and save custom components.
  • Model animation for validation and debugging.
  • Ability to save models as SAS data sets.
  • Wide variety of sampling distributions.

Genetic algorithms for local search optimisation
  • Genetic algorithms apply principles of natural selection and evolution in working with groups of solutions to optimisation problems.

Download the complete SAS/OR Fact Sheet.


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White paper

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