fmincon estimates gradients of objective and nonlinear constraint functions by taking finite differences. A finite difference calculation stepped outside the region where a function is well-defined, returning Inf, …

This tutorial includes multiple examples that show how to use two nonlinear optimization solvers, fminunc and fmincon, and how to set options. The principles outlined in this tutorial apply to the other …

Constrained Nonlinear Optimization Algorithms Constrained Optimization Definition Constrained minimization is the problem of finding a vector x that is a local minimum to a scalar function f (x) …

Nonlinear Constraints Several optimization solvers accept nonlinear constraints, including fmincon, fseminf, fgoalattain, fminimax, and the Global Optimization Toolbox solvers ga (Global Optimization …

The fmincon interior-point algorithm can accept a Hessian function as an input. When you supply a Hessian, you can obtain a faster, more accurate solution to a constrained minimization problem. The …

Nov 25, 2024 · "fmincon" is designed to minimize the objective function. If your objective function returns negative values (for example, objective = -1), "fmincon" will indeed try to make it more negative, …

Optimize Live Editor Task with fmincon Solver This example shows how to use the solver-based Optimize Live Editor task with the fmincon solver to minimize a quadratic subject to linear and …

Compare the performance of lsqnonlin and fmincon on a nonlinear least-squares problem with nonlinear constraints.

The algorithm can use sparse data; see Sparsity in Optimization Algorithms. The algorithm can use special techniques to save memory usage, such as a Hessian multiply function. For details, see …

Code Generation in fmincon Background What Is Code Generation? Code generation is the conversion of MATLAB ® code to C code using MATLAB Coder™. Code generation requires a MATLAB Coder …