Nonlinear Optimization

Solve constrained or unconstrained nonlinear problems with one or more objectives, in serial or parallel

Nonlinear optimization is minimizing or maximizing a nonlinear objective function subject to bound, linear, or nonlinear constraints. The constraints can be inequalities or equalities. Application areas include selecting optimal engineering designs, analyzing design tradeoffs, computing optimal trajectories for vehicles or robots, and financial portfolio optimization.

To set up a nonlinear optimization problem for solution, first decide between a problem-based approach and solver-based approach. See First Choose Problem-Based or Solver-Based Approach.

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Featured Examples

Tutorial for Optimization Toolbox

Tutorial for Optimization Toolbox

Tutorial example showing how to solve nonlinear problems and pass extra parameters.

Solve Constrained Nonlinear Optimization, Problem-Based

Solve Constrained Nonlinear Optimization, Problem-Based

Solve a constrained nonlinear problem based on optimization expressions. The example also shows how to convert a nonlinear function to an optimization expression.

Objective and Constraints Having a Common Function in Serial or Parallel, Problem-Based

Objective and Constraints Having a Common Function in Serial or Parallel, Problem-Based

Save time when the objective and nonlinear constraint functions share common computations in the problem-based approach.