Optimal solutions to complex business and planning problems. Fast.

A powerful array of optimization, simulation and project scheduling techniques for identifying actions that will get the best results, while operating within resource limitations and other relevant restrictions.

Robust, intuitive algebraic optimization modeling language

Enables you to produce a range of models, including linear, mixed integer linear, nonlinear, quadratic and network optimization, as well as solve constraint satisfaction problems.

A unified modeling language

Supports a wide range of optimization models with a single modeling and solution framework. You only need to learn one set of statements and commands to build a range of optimization and constraint satisfaction models.

Powerful optimization solvers and presolvers

Provides a suite of optimization solvers – all streamlined for simplicity and tuned for performance. Aggressive presolvers reduce effective problem size so you can tackle large problems and solve them more quickly.

Network flow optimization

Provides network algorithms, accessible from both PROC OPTMODEL and PROC OPTNETWORK, for investigating the characteristics of networks and finding the best answers to network-oriented problems.

Multistart algorithm for nonconvex nonlinear optimization

Increases chance of finding a globally optimal solution among many locally optimal solutions. Selects multiple starting points, begins optimization in parallel from each,  then reports the best solution from all starting points.

Decomposition algorithm (automated Dantzig-Wolfe)

Decomposes the overall problem into a set of component problems, each with an exclusive set of decision variables solved in parallel. Parallel solution of the subproblems is coordinated with the overall solution process, significantly reducing time to solution.

Black-box optimization

The black-box solver can be used with (generally nonlinear) optimization problems that don’t adhere to the assumptions that conventional optimization solvers make. Functions might be discontinuous, nonsmooth, computationally expensive to evaluate, based on black-box simulations, etc.

Constraint programming

Solves constraint satisfaction problems using domain reduction/constraint propagation and a choice of search strategies, such as look ahead and backtracking.

Accessible, cloud-enabled, in-memory engine

Uses the SAS Viya engine, which enhances the SAS Platform, providing high availability, fast in-memory processing, the ability to code from open source languages and native cloud support.

Consider more alternative actions and scenarios, and determine the best allocation of resources and plans for accomplishing goals.

Quickly solve complex optimization problems.

Find optimal solutions to difficult problems faster than ever. SAS Optimization takes advantage of the SAS® Viya® distributed, in-memory engine to deliver optimization modeling results at breakthrough speeds. In-memory data persistence eliminates the need to load data multiple times during iterative analyses. 

Drive better decision making.

Identify and apply the best responses to complex, real-world problems. State-of-the-art methods for mathematical optimization are integrated with a full suite of data preparation, exploration, analytics and reporting capabilities – all in one unified environment.

Empower users with their preferred programming language.

Python, Java, R and Lua programmers can take advantage of the wide range of solvers in SAS Optimization without having to learn SAS code. They can access powerful, trusted and tested SAS algorithms from the programming language they are most comfortable with.


이 새로운 솔루션은 폭넓고 깊이 있게 모든 분석 과제를 해결할 수 있는 최첨단 오픈 아키텍처인 SAS Viya를 기반으로 실행됩니다. 단일 클라우드 환경인 SAS Viya는 확장 가능하고 안전할 뿐만 아니라 애자일 IT 환경에 없어서는 안 될 분석 관리 및 거버넌스를 통해 데이터 사이언티스트에서 비즈니스 분석가까지, 그리고 애플리케이션 개발자에서 기업 임원에 이르기까지 누구나 이용할 수 있습니다. 분석 분야를 선도하는 세계적 리더인 SAS와 함께 여러분이 기대해왔던 성능을 경험해보세요.

Explore More on SAS® Optimization & Beyond



Learn how to use optimization to define weights and parameters for customer risk rating models.   


Read blog post



SAS is in the Leaders category in the 2019-2020 IDC MarketScape for general-purpose AI software platforms.


Read report



Ask questions, share tips and more in the Mathematical Optimization, Discrete-Event Simulation and OR Community.


Join community

분석 분야의 리더인 SAS 솔루션으로 시작하십시오.