Optimize business processes and address management science challenges
Project and resource scheduling
- 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 .
Discrete event simulation
- 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*.
Genetic algorithms for local search optimisation
- 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 apply principles of natural selection and evolution in working with groups of solutions to optimisation problems.
Download the complete SAS/OR Fact Sheet.