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SAS/OR®

SAS/OR Procedures and Solvers

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SAS/OR 14.3 Procedures and Solvers

For complete SAS/OR 14.3 documentation, go to the SAS/OR product documentation page.

Procedures

  • 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.

Solvers

  • 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.


More about This Product

SAS/OR 14.2 Procedures and Solvers

For complete SAS/OR 14.2 documentation, go to the SAS/OR product documentation page.

Procedures

  • 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

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.
    PDF   |   HTML


More about This Product Feedback

SAS/OR 14.1 Procedures and Solvers

For complete SAS/OR 14.1 documentation, go to the SAS/OR product documentation page.

Procedures

  • 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 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.
    PDF   |   HTML

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.
    PDF   |   HTML

Legacy Procedures and Solvers

  • 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.....xn)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


More about This Product Feedback

SAS/OR 13.2 Procedures and Solvers

For complete SAS/OR 13.2 documentation, go to the SAS/OR product documentation page.

Procedures

  • 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 programsproblems 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

Solvers

  • 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

Legacy Procedures and Solvers

  • 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.....xn)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]


More about This Product Feedback

SAS/OR 13.1 User's Guide - Procedures

For the complete SAS/OR 13.1 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 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 programsproblems 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]

Solvers

  • 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]

Legacy Procedures and Solvers

  • 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.....xn)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]


More about This Product Feedback

SAS/OR 12.3 User's Guide - Procedures

Note: SAS/OR 12.3 is essentially a maintenance release, with the exception that high-performance features for use in single-machine mode have been added. The SAS/OR 12.3 documentation applies to both SAS/OR 12.3 and 12.1.


For the complete SAS/OR 12.3 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 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 programsproblems 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]

Solvers

  • 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]

Legacy Procedures and Solvers

  • 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.....xn)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]


More about This Product Feedback

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 programsproblems 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]

Solvers

  • 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]

Legacy Procedures and Solvers

  • 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.....xn)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]