# Optimization Solver Routines

Intel® Math Kernel Library provides tools for solving optimization problems. These tools are routines for solving nonlinear least squares problems through the Trust-Region (TR) algorithms.

Intel MKL provides the optimization solver routines that can be used for:

- solving nonlinear least squares problems without constraints

- solving nonlinear least squares problems with boundary constraints

- computing the Jacobi matrix by central differences for solving nonlinear least squares problem

The first two groups of routines are designed to find only one local minimum point. However problems can have multiple local minima and trying different initial points is recommended for better solutions.

For more information on terms and key concepts required to understand the use of the Intel MKL nonlinear least squares problem solver routines, see Appendix “Optimization Solvers Basics”.

Routines described below are subdivided according to their purpose as follows:

Nonlinear Least Squares Problem without Constraints

Nonlinear Least Squares Problem with Linear (Boundary) Constraints

Jacobi Matrix Calculation Routines.