Documentation

This is machine translation

Translated by Microsoft
Mouse over text to see original. Click the button below to return to the English verison of the page.

Table for Choosing a Solver

Choose an optimizer based on problem characteristics and on the type of solution you want. Solver Characteristics contains more information to help you decide which solver is likely to be most suitable. This table gives recommendations that are suitable for most problems.

Problem TypeRecommended Solver
Smooth (objective twice differentiable), and you want a local solutionAn appropriate Optimization Toolbox™ solver; see Optimization Decision Table
Smooth (objective twice differentiable), and you want a global solution or multiple local solutionsGlobalSearch or MultiStart
Nonsmooth, and you want a local solutionpatternsearch
Nonsmooth, and you want a global solution or multiple local solutionspatternsearch with several initial points x0

To start patternsearch at multiple points when you have finite bounds lb and ub on every component, try

x0 = rand(size(lb)).*(ub - lb);

There are many other solvers with different solution algorithms, including the genetic algorithm solver ga and the particleswarm solver. Try some of them if the recommended solvers do not perform well on your problem. For details, see Global Optimization Toolbox Solver Characteristics.

More About

Was this topic helpful?