SAS/OR^®

SAS/OR 15.1 Procedures and Solvers

• The BOM Procedure  PDF   |   HTML
  Performs bill of material processing.
• The CLP Procedure  PDF   |   HTML
  Provides a finite-domain constraint programming solver for constraint satisfaction problems (CSPs) with linear, logical, global, and scheduling constraints.
• The CPM Procedure  PDF    HTML
  Used for planning, controlling, and monitoring a project.
• The DTREE Procedure  PDF   |   HTML
  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.
• The GA Procedure  PDF   |   HTML
  Enables implementation of the basic genetic algorithm by default, and uses other advanced techniques to handle constraints, accelerate convergence, and perform multiobjective optimizations.
• The GANTT Procedure  PDF   |   HTML
  Produces a Gantt chart, which is a graphical scheduling tool for the planning and control of a project.
  
• The NETDRAW Procedure  PDF   |   HTML
  Draws a network diagram of the activities in a project.
• The OPTLP Procedure  PDF   |   HTML
  Provides three methods of solving linear programs (LPs).
• The OPTLSO Procedure  PDF   |   HTML
  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.
  
• The OPTMILP Procedure  PDF   |   HTML
  Solve general mixed integer linear programs (MILPs).
• The OPTMODEL Procedure  PDF   |   HTML
  Comprises the powerful OPTMODEL modeling language and state-of-the-art solvers for several classes of mathematical programming problems.
• The OPTNET Procedure  PDF   |   HTML
  Analyzes relationships between entities.
  
• The OPTQP Procedure  PDF   |   HTML
  Solves quadratic programs which are problems that have a quadratic objective function and a collection of linear constraints, including lower and/or upper bounds on the decision variables.
• The PM Procedure  PDF   |   HTML
  Enables interactive planning, controlling, and monitoring of a project.

• The Constraint Programming (CLP) Solver   PDF   |   HTML
  Solves constraint satisfaction problems that have discrete variables and linear, logical, and global constraints. Specification of an objective function is optional.
  
• The Decomposition Algorithm  PDF   |   HTML
  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.
  
• The Linear Programming (LP) Solver  PDF   |   HTML
  Provides a framework for specifying and solving linear programs (LPs).
• The Mixed Integer Linear Programming (MILP) Solver  PDF   |   HTML
  Provides a framework for specifying and solving mixed integer linear programs (MILPs).
• The Network Solver  PDF   |   HTML
  Provides access to a set of graph theory and network optimization and analysis algorithms.
  
• The Nonlinear Programming (NLP) Solver  PDF   |   HTML
  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.
• The Quadratic Programming (QP) Solver  PDF   |   HTML
  Provides a framework for specifying and solving quadratic programs.
  

SAS/OR 14.3 Procedures and Solvers

• The BOM Procedure  PDF   |   HTML
  Performs bill of material processing.
• The CLP Procedure  PDF   |   HTML
  A finite-domain constraint programming solver for constraint satisfaction problems (CSPs) with linear, logical, global, and scheduling constraints.
• The CPM Procedure  PDF    HTML
  Used for planning, controlling, and monitoring a project.
• The DTREE Procedure  PDF   |   HTML
  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.
• The GA Procedure  PDF   |   HTML
  Enables implementation of the basic genetic algorithm by default, and to employ other advanced techniques to handle constraints, accelerate convergence, and perform multiobjective optimizations.
• The GANTT Procedure  PDF   |   HTML
  Produces a Gantt chart, which is a graphical scheduling tool for the planning and control of a project.
  
• The NETDRAW Procedure  PDF   |   HTML
  Draws a network diagram of the activities in a project.
• The OPTLP Procedure  PDF   |   HTML
  Provides three methods of solving linear programs (LPs).
• The OPTLSO Procedure  PDF   |   HTML
  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.
  
• The OPTMILP Procedure  PDF   |   HTML
  The OPTMILP procedure is a solver for general mixed integer linear programs (MILPs).
• The OPTMODEL Procedure  PDF   |   HTML
  Comprises the powerful OPTMODEL modeling language and state-of-the-art solvers for several classes of mathematical programming problems.
• The OPTNET Procedure  PDF   |   HTML
  Used to analyze relationships between entities.
  
• The OPTQP Procedure  PDF   |   HTML
  Solves quadratic programs-problems with quadratic objective function and a collection of linear constraints, including lower and/or upper bounds on the decision variables.
• The PM Procedure  PDF   |   HTML
  An interactive procedure that can be used for planning, controlling, and monitoring a project.

• The Constraint Programming (CLP) Solver   PDF   |   HTML
  A solver for constraint satisfaction problems with discrete variables and linear, logical, and global constraints. Specification of an objective function is optional.
  
• The Decomposition Algorithm  PDF   |   HTML
  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.
  
• The Linear Programming (LP) Solver  PDF   |   HTML
  Provides a framework for specifying and solving linear programs (LPs).
• The Mixed Integer Linear Programming (MILP) Solver  PDF   |   HTML
  Provides a framework for specifying and solving mixed integer linear programs (MILPs).
• The Network Solver  PDF   |   HTML
  Provides access to a set of graph theory and network optimization and analysis algorithms.
  
• The Nonlinear Programming (NLP) Solver  PDF   |   HTML
  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.
• The Quadratic Programming (QP) Solver  PDF   |   HTML
  Provides a framework for specifying and solving quadratic programs.
  

SAS/OR 14.2 Procedures and Solvers

• The BOM Procedure
  Performs bill of material processing.
  PDF   |   HTML
• The CLP Procedure
  A finite-domain 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 state-of-the-art 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 programs-problems 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.
  PDF   |   HTML

• 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.
  PDF   |   HTML

SAS/OR 14.1 Procedures and Solvers

• The BOM Procedure
  Performs bill of material processing.
  PDF   |   HTML
• The CLP Procedure
  A finite-domain 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 state-of-the-art 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 programs�problems 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.
  PDF   |   HTML

• 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.
  PDF   |   HTML

• The INTPOINT Procedure
  Solves the Network Program with Side Constraints (NPSC) problem and the more general Linear Programming (LP) problem.
  PDF   |   HTML
• The LP Procedure
  Solves linear programs, integer programs, and mixed-integer programs. It also performs parametric programming and range analysis, and it reports on solution sensitivity to changes in the right-hand-side constants and price coefficients.
  PDF   |   HTML
• The NETFLOW Procedure
  Accepts the network specification in a format that is particularly suited to networks.
  PDF   |   HTML
• The NLP Procedure
  Offers a set of optimization techniques for minimizing or maximizing a continuous nonlinear function f(x) of n decision variables, x = (x₁.....x_n)^T with lower and upper bound, linear and nonlinear, equality and inequality constraints.
  PDF   |   HTML
• The NLPC Nonlinear Optimization (NLPC) Solver
  Solves unconstrained nonlinear optimization problems and problems with a nonlinear objective function subject to bound, linear, or nonlinear constraints. It provides several optimization techniques that effectively handle these classes of problems. HTML
• The Unconstrained Nonlinear Programming (NLPU) Solver
  Used for solving general unconstrained nonlinear programming (NLP) problems. HTML
• The Sequential Quadratic Programming (SQP) Solver
  The sequential quadratic programming (SQP) solver is a component of the OPTMODEL procedure, and it can be used for solving general nonlinear programming (NLP) problems. HTML

SAS/OR 13.2 Procedures and Solvers

• The BOM Procedure
  Performs bill of material processing.
  PDF (4.98MB)  |   HTML
• The CLP Procedure
  A finite-domain constraint programming solver for constraint satisfaction problems (CSPs) with linear, logical, global, and scheduling constraints.
  PDF (5.28MB)  |   HTML
• The CPM Procedure
  Used for planning, controlling, and monitoring a project.
  PDF (1328MB)  |   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 (7.01MB)  |   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 (22.1MB)  |   HTML
• The GANTT Procedure
  Produces a Gantt chart, which is a graphical scheduling tool for the planning and control of a project.
  PDF (132MB)  |   HTML
• The NETDRAW Procedure
  Draws a network diagram of the activities in a project.
  PDF (5.69MB)  |   HTML
• The OPTLP Procedure
  Provides three methods of solving linear programs (LPs).
  PDF (4.25MB)  |   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 (2.73MB)  |   HTML
• The OPTMILP Procedure
  The OPTMILP procedure is a solver for general mixed integer linear programs (MILPs).
  PDF (3.9MB)  |   HTML
• The OPTMODEL Procedure
  Comprises the powerful OPTMODEL modeling language and state-of-the-art solvers for several classes of mathematical programming problems.
  PDF (11.4MB)  |   HTML
• The OPTNET Procedure
  Used to analyze relationships between entities.
  PDF (7.75MB)  |   HTML
• The OPTQP Procedure
  Solves quadratic programs�problems with quadratic objective function and a collection of linear constraints, including lower and/or upper bounds on the decision variables.
  PDF (3.34MB)  |   HTML
• The PM Procedure
  An interactive procedure that can be used for planning, controlling, and monitoring a project.
  PDF (132MB)  |   HTML

• The Constraint Programming (CLP) Solver (Experimental)
  A solver for constraint satisfaction problems with discrete variables and linear, logical, and global constraints. Specification of an objective function is optional.
  PDF (4.24MB)  |   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 (7.23MB)  |   HTML
• The Linear Programming (LP) Solver
  Provides a framework for specifying and solving linear programs (LPs).
  PDF (6.5MB)  |   HTML
• The Mixed Integer Linear Programming (MILP) Solver
  Provides a framework for specifying and solving mixed integer linear programs (MILPs).
  PDF (3.58B)  |   HTML
• The Network Solver
  Provides access to a set of graph theory and network optimization and analysis algorithms.
  PDF (7.44MB)  |   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 (5.63MB)  |   HTML
• The Quadratic Programming (QP) Solver
  Provides a framework for specifying and solving quadratic programs.
  PDF (3.6MB)  |   HTML

• The INTPOINT Procedure
  Solves the Network Program with Side Constraints (NPSC) problem and the more general Linear Programming (LP) problem.
  PDF (66.5MB)  |   HTML
• The LP Procedure
  Solves linear programs, integer programs, and mixed-integer programs. It also performs parametric programming and range analysis, and it reports on solution sensitivity to changes in the right-hand-side constants and price coefficients.
  PDF (8.07MB)  |   HTML
• The NETFLOW Procedure
  Accepts the network specification in a format that is particularly suited to networks.
  PDF (8.93MB)  |   HTML
• The NLP Procedure
  Offers a set of optimization techniques for minimizing or maximizing a continuous nonlinear function f(x) of n decision variables, x = (x₁.....x_n)^T with lower and upper bound, linear and nonlinear, equality and inequality constraints.
  PDF (10.01MB)  |   HTML
• The Interior Point NLP (IPNLP) Solver
  Can solve nonlinear programming (NLP) problems that contain both nonlinear equality and inequality constraints. [HTML]
• The NLPC Nonlinear Optimization (NLPC) Solver
  Solves unconstrained nonlinear optimization problems and problems with a nonlinear objective function subject to bound, linear, or nonlinear constraints. It provides several optimization techniques that effectively handle these classes of problems. [HTML]
• The Unconstrained Nonlinear Programming (NLPU) Solver
  Used for solving general unconstrained nonlinear programming (NLP) problems. [HTML]
• The Sequential Quadratic Programming (SQP) Solver
  The sequential quadratic programming (SQP) solver is a component of the OPTMODEL procedure, and it can be used for solving general nonlinear programming (NLP) problems. [HTML]

SAS/OR 13.1 User's Guide - Procedures

• The BOM Procedure
  Performs bill of material processing. [HTML]
• The CLP Procedure
  A finite-domain constraint programming solver for constraint satisfaction problems (CSPs) with linear, logical, global, and scheduling constraints. [HTML]
• The CPM Procedure
  Used for planning, controlling, and monitoring a project. [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. [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. [HTML]
• The GANTT Procedure
  Produces a Gantt chart, which is a graphical scheduling tool for the planning and control of a project. [HTML]
• The NETDRAW Procedure
  Draws a network diagram of the activities in a project. [HTML]
• The OPTLP Procedure
  Provides three methods of solving linear programs (LPs). [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. [HTML]
• The OPTMILP Procedure
  The OPTMILP procedure is a solver for general mixed integer linear programs (MILPs). [HTML]
• The OPTMODEL Procedure
  Comprises the powerful OPTMODEL modeling language and state-of-the-art solvers for several classes of mathematical programming problems. [HTML]
• The OPTNET Procedure
  Used to analyze relationships between entities. [HTML]
• The OPTQP Procedure
  Solves quadratic programs�problems with quadratic objective function and a collection of linear constraints, including lower and/or upper bounds on the decision variables. [HTML]
• The PM Procedure
  An interactive procedure that can be used for planning, controlling, and monitoring a project. [HTML]

• The Linear Programming (LP) Solver
  Provides a framework for specifying and solving linear programs (LPs). [HTML]
• The Mixed Integer Linear Programming (MILP) Solver
  Provides a framework for specifying and solving mixed integer linear programs (MILPs). [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. [HTML]
• The Quadratic Programming (QP) Solver
  Provides a framework for specifying and solving quadratic programs. [HTML]

• The INTPOINT Procedure
  Solves the Network Program with Side Constraints (NPSC) problem and the more general Linear Programming (LP) problem. [HTML]
• The LP Procedure
  Solves linear programs, integer programs, and mixed-integer programs. It also performs parametric programming and range analysis, and it reports on solution sensitivity to changes in the right-hand-side constants and price coefficients. [HTML]
• The NETFLOW Procedure
  Accepts the network specification in a format that is particularly suited to networks. [HTML]
• The NLP Procedure
  Offers a set of optimization techniques for minimizing or maximizing a continuous nonlinear function f(x) of n decision variables, x = (x₁.....x_n)^T with lower and upper bound, linear and nonlinear, equality and inequality constraints. [HTML]
• The Interior Point NLP (IPNLP) Solver
  Can solve nonlinear programming (NLP) problems that contain both nonlinear equality and inequality constraints. [HTML]
• The NLPC Nonlinear Optimization (NLPC) Solver
  Solves unconstrained nonlinear optimization problems and problems with a nonlinear objective function subject to bound, linear, or nonlinear constraints. It provides several optimization techniques that effectively handle these classes of problems. [HTML]
• The Unconstrained Nonlinear Programming (NLPU) Solver
  Used for solving general unconstrained nonlinear programming (NLP) problems. [HTML]
• The Sequential Quadratic Programming (SQP) Solver
  The sequential quadratic programming (SQP) solver is a component of the OPTMODEL procedure, and it can be used for solving general nonlinear programming (NLP) problems. [HTML]

SAS/OR 12.3 User's Guide - Procedures

• The BOM Procedure
  Performs bill of material processing. [HTML]
• The CLP Procedure
  A finite-domain constraint programming solver for constraint satisfaction problems (CSPs) with linear, logical, global, and scheduling constraints. [HTML]
• The CPM Procedure
  Used for planning, controlling, and monitoring a project. [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. [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. [HTML]
• The GANTT Procedure
  Produces a Gantt chart, which is a graphical scheduling tool for the planning and control of a project. [HTML]
• The NETDRAW Procedure
  Draws a network diagram of the activities in a project. [HTML]
• The OPTLP Procedure
  Provides three methods of solving linear programs (LPs). [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. [HTML]
• The OPTMILP Procedure
  The OPTMILP procedure is a solver for general mixed integer linear programs (MILPs). [HTML]
• The OPTMODEL Procedure
  Comprises the powerful OPTMODEL modeling language and state-of-the-art solvers for several classes of mathematical programming problems. [HTML]
• The OPTNET Procedure
  Used to analyze relationships between entities. [HTML]
• The OPTQP Procedure
  Solves quadratic programs�problems with quadratic objective function and a collection of linear constraints, including lower and/or upper bounds on the decision variables. [HTML]
• The PM Procedure
  An interactive procedure that can be used for planning, controlling, and monitoring a project. [HTML]

• The Linear Programming (LP) Solver
  Provides a framework for specifying and solving linear programs (LPs). [HTML]
• The Mixed Integer Linear Programming (MILP) Solver
  Provides a framework for specifying and solving mixed integer linear programs (MILPs). [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. [HTML]
• The Quadratic Programming (QP) Solver
  Provides a framework for specifying and solving quadratic programs. [HTML]

• The INTPOINT Procedure
  Solves the Network Program with Side Constraints (NPSC) problem and the more general Linear Programming (LP) problem. [HTML]
• The LP Procedure
  Solves linear programs, integer programs, and mixed-integer programs. It also performs parametric programming, range analysis, and reports on solution sensitivity to changes in the right-hand-side constants and price coefficients. [HTML]
• The Interior Point NLP (IPNLP) Solver
  Can solve nonlinear programming (NLP) problems that contain both nonlinear equality and inequality constraints. [HTML]
• The NETFLOW Procedure
  Accepts the network specification in a format that is particularly suited to networks. [HTML]
• The NLP Procedure
  Offers a set of optimization techniques for minimizing or maximizing a continuous nonlinear function f(x) of n decision variables, x = (x₁.....x_n)^T with lower and upper bound, linear and nonlinear, equality and inequality constraints. [HTML]
• The NLPC Nonlinear Optimization (NLPC) Solver
  Solves unconstrained nonlinear optimization problems and problems with a nonlinear objective function subject to bound, linear, or nonlinear constraints. It provides several optimization techniques that effectively handle these classes of problems. [HTML]
• The Unconstrained Nonlinear Programming (NLPU) Solver
  Used for solving general unconstrained nonlinear programming (NLP) problems. [HTML]
• The Sequential Quadratic Programming (SQP) Solver
  The sequential quadratic programming (SQP) solver is a component of the OPTMODEL procedure, and it can be used for solving general nonlinear programming (NLP) problems. [HTML]

For the complete SAS/OR 9.3 User's Guide: Mathematical Programming, go to the SAS/OR product documentation page.

Procedures

• The BOM Procedure
  Performs bill of material processing. [HTML]
• The CLP Procedure
  A finite-domain constraint programming solver for constraint satisfaction problems (CSPs) with linear, logical, global, and scheduling constraints. [HTML]
• The CPM Procedure
  Used for planning, controlling, and monitoring a project. [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. [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. [HTML]
• The GANTT Procedure
  Produces a Gantt chart, which is a graphical scheduling tool for the planning and control of a project. [HTML]
• The NETDRAW Procedure
  Draws a network diagram of the activities in a project. [HTML]
• The OPTLP Procedure
  Provides three methods of solving linear programs (LPs). [HTML]
• The OPTMILP Procedure
  The OPTMILP procedure is a solver for general mixed integer linear programs (MILPs). [HTML]
• The OPTMODEL Procedure
  Comprises the powerful OPTMODEL modeling language and state-of-the-art solvers for several classes of mathematical programming problems. [HTML]
• The OPTQP Procedure
  Solves quadratic programs�problems with quadratic objective function and a collection of linear constraints, including lower and/or upper bounds on the decision variables. [HTML]
• The PM Procedure
  An interactive procedure that can be used for planning, controlling, and monitoring a project. [HTML]

• The Linear Programming (LP) Solver
  Provides a framework for specifying and solving linear programs (LPs). [HTML]
• The Mixed Integer Linear Programming (MILP) Solver
  Provides a framework for specifying and solving mixed integer linear programs (MILPs). [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. [HTML]
• The Quadratic Programming (QP) Solver
  Provides a framework for specifying and solving quadratic programs. [HTML]

• The INTPOINT Procedure
  Solves the Network Program with Side Constraints (NPSC) problem and the more general Linear Programming (LP) problem. [HTML]
• The LP Procedure
  Solves linear programs, integer programs, and mixed-integer programs. It also performs parametric programming, range analysis, and reports on solution sensitivity to changes in the right-hand-side constants and price coefficients. [HTML]
• The Interior Point NLP (IPNLP) Solver
  Can solve nonlinear programming (NLP) problems that contain both nonlinear equality and inequality constraints. [HTML]
• The NETFLOW Procedure
  Accepts the network specification in a format that is particularly suited to networks. [HTML]
• The NLP Procedure
  Offers a set of optimization techniques for minimizing or maximizing a continuous nonlinear function f(x) of n decision variables, x = (x₁.....x_n)^T with lower and upper bound, linear and nonlinear, equality and inequality constraints. [HTML]
• The NLPC Nonlinear Optimization (NLPC) Solver
  Solves unconstrained nonlinear optimization problems and problems with a nonlinear objective function subject to bound, linear, or nonlinear constraints. It provides several optimization techniques that effectively handle these classes of problems. [HTML]
• The Unconstrained Nonlinear Programming (NLPU) Solver
  Used for solving general unconstrained nonlinear programming (NLP) problems. [HTML]
• The Sequential Quadratic Programming (SQP) Solver
  The sequential quadratic programming (SQP) solver is a component of the OPTMODEL procedure, and it can be used for solving general nonlinear programming (NLP) problems. [HTML]