**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.

**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.

**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 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用roblems 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*= (*x*)_{1}.....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

**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用roblems 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*= (*x*)_{1}.....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]

**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用roblems 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*= (*x*)_{1}.....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]

For the complete

**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用roblems 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*= (*x*)_{1}.....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.

**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用roblems 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*= (*x*)_{1}.....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]