Identify which actions will produce the best results – given constraints – using optimization, simulation and project scheduling techniques. With our operations research software, you can consider more options and scenarios, determine the best allocation of resources and implement the best plans for accomplishing goals.
Identify the best answers to planning problems.
Get the broadest spectrum of operations research modeling and solution techniques available, including state-of-the-art methods for mathematical optimization. The depth of detail and realism in the software's modeling capabilities, combined with control of optimization, simulation and scheduling processes, and an integrated approach to data access and information delivery, enable you to identify and apply the best responses to complex planning problems.
Build models interactively, and experiment with data.
Interactively build models, modify constraints or variables, and experiment easily with the effects of changes to underlying data. In mathematical optimization, a specialized modeling language enables you to work transparently and directly with symbolic problem formulations, and the software automatically chooses the most appropriate solution method for the current problem. This allows you to formulate and solve problems intuitively and efficiently, regardless of their specific mathematical form.
Easily incorporate more data.
SAS/OR makes it is easy to indicate where and how a model will use input data. Data/model separation is maintained, which is critical when reusing models or model components. Users can select which aspects of the solution get reported and can control the form in which they are reported.
Get faster, better answers.
Confidently manage projects to meet deadlines within resource limitations, and create back-up plans to address unforeseen variations in resource availability. SAS/OR includes analytic and solution methods that are tuned to address even the largest, most complex real-world problems.
- Mathematical optimization. Contains sophisticated mathematical programming techniques that can help determine the best use of limited resources to achieve goals and objectives.
- Global/local search optimization and constraint programming. Applies multiple global and local search algorithms in parallel to solve difficult optimization problems. Solves constraint satisfaction problems.
- Discrete event simulation. Provides all the tools needed for building, executing and analyzing discrete-event simulation models, via a user-friendly interface.
- Project and resource scheduling. Gives you the flexibility to plan, manage and track project and resource schedules through a single, integrated system.