Solve problems that have multiple objectives by the goal attainment
method. For this method, you choose a goal for each objective, and the
solver attempts to find a point that satisfies all goals simultaneously,
or has relatively equal dissatisfaction. One important special case of
this problem is to minimize the maximum objective, and this problem has
a special solver,
|Optimize||Optimize or solve equations in the Live Editor|
Example showing how to plot a Pareto front in a two-objective problem.
Shows how minimax problems are solved better by the dedicated
fminimax function than by solvers for smooth
This example shows how to solve a pole-placement problem using multiobjective goal attainment.
Example showing how to minimize the maximum discrepancy in a simulation.
Example showing filter design using multiobjective goal attainment.
This example shows how to solve a nonlinear filter design problem.
Use multiple processors for optimization.
Perform gradient estimation in parallel.
Investigate factors for speeding optimizations.
Minimizing multiple objective functions in n dimensions.
Reformulate some nonsmooth functions as smooth functions by using auxiliary variables.
Explore optimization options.