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,
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.
Using multiple processors for optimization.
Automatic gradient estimation in parallel.
Considerations for speeding optimizations.