Optimization Techniques in MATLAB

Day 1 of 1

Running an Optimization Problem

Objective:Understand the basic structure and process of solving optimization problems effectively. Use interactive tools to define and solve optimization problems.

• Identifying the problem components
• Running an optimization using the Live Editor Optimization Task
• Applying the optimization process
• Using optimization functions

Specifying Objective Functions and Constraints

Objective:Write an optimization problem. Use problem-based workflow to arrive at a solution.

• Using the problem-based workflow
• Specifying objective functions and constraints
• Identifying different types of constraints

Choosing a Solver and Improving Performance

Objective:Select an appropriate solver and algorithm by considering the type of optimization problem to be solved. Interpret the output from the solver and diagnose the progress of an optimization.

• Classifying the objective
• Choosing a solver and algorithm
• Examining and interpreting the result
• Providing derivative information

Global and Multiobjective Optimization

Objective:Use Global Optimization Toolbox functionality to solve problems where classical algorithms fail or work inefficiently. Solve problems with many objectives.

• Finding the global minimum
• Using genetic algorithms, direct search methods and surrogate optimization
• Use multiobjective solvers