# Multiobjective Optimization

Solve multiobjective optimization problems in serial or parallel

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, `fminimax`.

## Functions

 `fgoalattain` Solve multiobjective goal attainment problems `fminimax` Solve minimax constraint problem

## Topics

### Multiobjective Solutions

Generate and Plot a Pareto Front

Example showing how to plot a Pareto front in a two-objective problem.

Compare fminimax and fminunc

Shows how minimax problems are solved better by the dedicated `fminimax` function than by solvers for smooth problems.

Multi-Objective Goal Attainment Optimization

This example shows how to solve a pole-placement problem using multiobjective goal attainment.

Using fminimax with a Simulink Model

Example showing how to minimize the maximum discrepancy in a simulation.

Signal Processing Using fgoalattain

Example showing filter design using multiobjective goal attainment.

Minimax Optimization

This example shows how to solve a nonlinear filter design problem.

### Parallel Computing

What Is Parallel Computing in Optimization Toolbox?

Use multiple processors for optimization.

Using Parallel Computing in Optimization Toolbox

Improving Performance with Parallel Computing

Investigate factors for speeding optimizations.

### Algorithms and Other Theory

Multiobjective Optimization Algorithms

Minimizing multiple objective functions in n dimensions.

Optimization Options Reference

Explore optimization options.

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