Problem-Based Nonlinear Programming - Mathematical Modeling with Optimization, Part 4
Express and solve a nonlinear optimization problem with the problem-based approach of Optimization Toolbox™.
- Solve Constrained Nonlinear Optimization, Problem-Based Documentation: http://bit.ly/2Ll5wyk
Interactively define the variables, objective function, and constraints to reflect the mathematical statement of the nonlinear program.
Start by creating an optimization problem to hold the problem. Next, define optimization variables and their bounds. Each optimization variable has its own display name, dimension, type, and bounds. Define one or more scalar or array variables to match the variables used in the mathematical statement.
Create the objective and constraints with optimization expressions built with the optimization variables. Specify them directly for rational expressions. Specify other expressions with MATLAB® functions and convert into optimization expressions with a conversion function. The conversion facility makes it easy to define an optimization problem using existing functions.
Use the display functions to review the completed optimization problem. Then specify an initial point and solve. The type of solver is automatically selected based on the type of variables, objective, and constraints, relieving you of needing to know the many available solvers.
- Solve Constrained Nonlinear Optimization, Problem-Based Documentation: http://bit.ly/2Ll5wyk
Interactively define the variables, objective function, and constraints to reflect the mathematical statement of the nonlinear program.
Start by creating an optimization problem to hold the problem. Next, define optimization variables and their bounds. Each optimization variable has its own display name, dimension, type, and bounds. Define one or more scalar or array variables to match the variables used in the mathematical statement.
Create the objective and constraints with optimization expressions built with the optimization variables. Specify them directly for rational expressions. Specify other expressions with MATLAB® functions and convert into optimization expressions with a conversion function. The conversion facility makes it easy to define an optimization problem using existing functions.
Use the display functions to review the completed optimization problem. Then specify an initial point and solve. The type of solver is automatically selected based on the type of variables, objective, and constraints, relieving you of needing to know the many available solvers.
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