This example shows how to create a rational objective function using optimization variables and solve the resulting unconstrained problem.
This example shows how to solve a constrained nonlinear problem based on optimization expressions. The example also shows how to convert a nonlinear function to an optimization expression.
Convert nonlinear functions, whether expressed as function files or anonymous
functions, by using
Shows how to define objective and constraint functions for a structured nonlinear optimization in the problem-based approach.
Shows how to use optimization variables to create linear constraints, and
fcn2optimexpr to convert a function to an optimization
How to include derivative information in problem-based optimization when automatic derivatives do not apply.
Save time when your objective and nonlinear constraint functions share common computations in the problem-based approach.
Solve a feasibility problem, which is a problem with constraints only.
Shows how to use an output function in the problem-based approach to record iteration history and to make a custom plot.
Use multiple processors for optimization.
Perform gradient estimation in parallel.
Investigate factors for speeding optimizations.
优化仿真、黑盒目标函数或 ODE 时的特殊注意事项。
在无约束的情况下，在 n 个维度中最小化单目标函数。
在有各种约束的情况下，在 n 个维度中最小化单目标函数。
fminsearch takes to
minimize a function.
Lists published materials that support concepts implemented in the solver algorithms.