SAS/OR^{®}
SAS/OR 14.2

Procedures
 The BOM Procedure
Performs bill of material processing.
PDF  HTML  The CLP Procedure
A finitedomain constraint programming solver for constraint satisfaction problems (CSPs) with linear, logical, global, and scheduling constraints.
PDF  HTML  The CPM Procedure
Used for planning, controlling, and monitoring a project.
PDF  HTML  The DTREE Procedure
An interactive procedure for decision analysis, it interprets a decision problem represented in SAS data sets, finds the optimal decisions, and plots on a line printer or a graphics device the decision tree showing the optimal decisions.
PDF  HTML  The GA Procedure
Enables implementation of the basic genetic algorithm by default, and to employ other advanced techniques to handle constraints, accelerate convergence, and perform multiobjective optimizations.
PDF  HTML  The GANTT Procedure
Produces a Gantt chart, which is a graphical scheduling tool for the planning and control of a project.
PDF  HTML  The NETDRAW Procedure
Draws a network diagram of the activities in a project.
PDF  HTML  The OPTLP Procedure
Provides three methods of solving linear programs (LPs).
PDF  HTML  The OPTLSO Procedure
Performs parallel hybrid global or local search optimization to solve problems that have "black box" objective functions, continuous or discrete decision variables, and linear or nonlinear constraints.
PDF  HTML  The OPTMILP Procedure
The OPTMILP procedure is a solver for general mixed integer linear programs (MILPs).
PDF  HTML  The OPTMODEL Procedure
Comprises the powerful OPTMODEL modeling language and stateoftheart solvers for several classes of mathematical programming problems.
PDF  HTML  The OPTNET Procedure
Used to analyze relationships between entities.
PDF  HTML  The OPTQP Procedure
Solves quadratic programsproblems with quadratic objective function and a collection of linear constraints, including lower and/or upper bounds on the decision variables.
PDF  HTML  The PM Procedure
An interactive procedure that can be used for planning, controlling, and monitoring a project.
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Solvers
 The Constraint Programming (CLP) Solver
A solver for constraint satisfaction problems with discrete variables and linear, logical, and global constraints. Specification of an objective function is optional.
PDF  HTML  The Decomposition Algorithm
Provides an alternative method for solving linear or mixed integer linear optimization problems, exploiting special structure in the constraint matrix and solving subproblems in parallel.
PDF  HTML  The Linear Programming (LP) Solver
Provides a framework for specifying and solving linear programs (LPs).
PDF  HTML  The Mixed Integer Linear Programming (MILP) Solver
Provides a framework for specifying and solving mixed integer linear programs (MILPs).
PDF  HTML  The Network Solver
Provides access to a set of graph theory and network optimization and analysis algorithms.
PDF  HTML  The Nonlinear Programming (NLP) Solver
The sparse nonlinear programming (NLP) solver is a component of the OPTMODEL procedure that can solve optimization problems containing both nonlinear equality and inequality constraints.
PDF  HTML  The Quadratic Programming (QP) Solver
Provides a framework for specifying and solving quadratic programs.
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Topics
SAS/OR Documentation Examples
For examples in the documentation, go to SAS/OR software documentation examples.SAS/OR Software Examples
The following SAS/OR software examples are not included in the SAS/OR documentation and are available only on the Web.
Videos
Air date: January 25, 2016 
Air date: February 11, 2015 
Air date: November 20, 2014 
Air date: December 10, 2013 
Air date: July 10, 2013 
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Air date:July 10, 2013 
2016 Papers
 Solving Business Problems with SAS Analytics and OPTMODEL
Hughes, Ed; Pratt, Rob; Shuler, Scott; Koch, Patrick; SAS Institute, Inc. 2016This presentation explores practical applications of building and solving mathematical optimization models with PROC OPTMODEL, and also describes how optimization methods are being used to improve predictive machine learning models.
 Solving Business Problems with SAS Analytics and OPTMODEL
Hughes, Ed; Pratt, Rob; Tutunchi, Golbarg; SAS Institute, Inc. 2016Classical and practical examples demonstrate OPTMODEL's power and versatility in building and solving optimization models in a variety of settings. Includes a survey of recent consulting projects, highlighting our transportation optimization work with Boston Public Schools.
 Using the OPTMODEL Procedure in SAS/OR to Find the k Best Solutions
Pratt, Rob; SAS Institute, Inc. 2016This paper uses various techniques for finding the k best solutions to the linear assignment problem in order to illustrate several features recently added to the OPTMODEL procedure in SAS/OR software.
 Using SAS Simulation Studio to Test and Validate SAS/OR Optimization Models
Hughes, Ed; Lada, Emily; Lopes, Leo; Pólik, Imre ; SAS Institute, Inc. 2016This paper begins with a look at both optimization modeling and discreteevent simulation modeling, and explores how they can most effectively work together to create additional analytic value. It then considers two examples of a combined optimization and simulation approach and discusses the resulting benefits.
SAS/OR software integrates essential optimization, scheduling, simulation, and related modeling and solution capabilities in an adaptable environment. Its powerful set of management science solutions provide companies the knowledge they need to identify and optimize business processes and management challenges. SAS/OR software is designed for people with operations research/management science or similar training who are seeking to build and solve decision guidance models that use one or more of the following operations research techniques:
 mathematical programming
 discrete event simulation
 project and resource scheduling
 local search optimization
 decision analysis
 billofmaterial (BOM) processing
These capabilities are supported and complemented by SAS software's strengths in data access and integration, analytics, and business intelligence. SAS/OR software tools also form the heart of optimization solutions such as SAS Marketing Optimization and SAS Revenue Optimization Suite. Some of the many applications that lend themselves to the use of SAS/OR tools include the following:
 project planning
 management information systems
 resource allocation and management
 financial planning
 production planning and inventory control
 supply chain management and optimization
 transportation and distribution planning
 material resource planning
 job shop scheduling
To see some uses of SAS/OR software in applications that address business planning problems, try out the supply chain optimization demos.