Optimization Techniques in MATLAB
View schedule and enrollCourse Details
- Running optimization problems in MATLAB
- Specifying objective functions and constraints
- Solvers and performance
- Global and multiobjective optimization
This program has been approved by GARP and qualifies for 7 GARP CPD credit hours. If you are a Certified FRM or ERP, please record this activity in your credit tracker.
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
Solvers and 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
- Use 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
Level: Intermediate
Prerequisites:
- MATLAB Fundamentals
- Knowledge of linear algebra and multivariate calculus is helpful.
Duration: 1 day
Languages: Deutsch, English, 日本語, 한국어
