Surrogate Optimization

Surrogate optimization solver for expensive objective functions

Use surrogate optimization for expensive (time-consuming) objective functions. The solver accepts only bound constraints, and requires finite bounds on all variables. The solver can optionally save its state after each function evaluation, enabling recovery from premature stops.

Functions

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surrogateoptSurrogate optimization for global minimization of time-consuming objective functions
optimoptionsCreate optimization options
resetoptionsReset options

Topics

Optimize Using Surrogate Optimization

Surrogate Optimization of Multidimensional Function

Solve a multidimensional problem using surrogateopt, patternsearch, and fmincon, and then compare the results.

Modify surrogateopt Options

Search for the global minimum using surrogateopt, and then modify options of the function to revise the search.

Interpret surrogateoptplot

How to interpret a surrogateoptplot plot.

Compare Surrogate Optimization with Other Solvers

Compare surrogateopt to patternsearch and fmincon on a nonsmooth problem.

Surrogate Optimization of Six-Element Yagi-Uda Antenna

Solve an antenna design problem using surrogate optimization.

Work with Checkpoint Files

Shows how to use checkpoint files to restart, recover, analyze, or extend an optimization.

Surrogate Optimization with Nonlinear Constraint

Solve a problem containing a nonlinear ODE with a nonlinear constraint using surrogateopt.

Surrogate Optimization Background

What Is Surrogate Optimization?

Surrogate optimization attempts to find a global minimum of an objective function using few objective function evaluations.

Surrogate Optimization Algorithm

Learn details of the surrogate optimization algorithm, when run in serial or parallel.

Surrogate Optimization Options

Explore the options for surrogate optimization, including algorithm control, stopping criteria, command-line display, and output and plot functions.

Related Information