fmincon passes x to your objective function and any nonlinear constraint functions in the shape of the x0 argument. For example, if x0 is a 5-by-3 array, then fmincon passes x to fun as a 5-by-3 …

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 …

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

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 …

This example shows how to solve a nonlinear problem with nonlinear constraints using derivative information. Ordinarily, minimization routines use numerical gradients calculated by finite …

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 …

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 …

Tolerances and Stopping Criteria The number of iterations in an optimization depends on a solver's stopping criteria. These criteria include several tolerances you can set. Generally, a …

Additionally, to make the history available outside of the fmincon function, perform the optimization inside a nested function that calls fmincon and returns the output function …

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 …