MATLAB and Simulink Training

Optimization Techniques in MATLAB

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Course Details

This one-day course introduces applied optimization in the MATLAB® environment, focusing on using Optimization Toolbox™ and Global Optimization Toolbox. Topics include:
 
  • 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:

Duration: 1 day

Languages: English

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