MATLAB & Simulink


Optimization Techniques in MATLAB

Course Highlights

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

  • Choosing solvers and improving performance

  • Global and multiobjective optimization

Who Should Attend 

Scientist, engineers, researchers, manager, and analyst from various industries and
government bodies who are interested to gain a fundamental understanding of the
concepts, applications and techniques of optimization and/or plan to apply optimization
in their designs, processes, projects, services and work systems.


Course Prerequisites

MATLAB Fundamentals
Course Benefits

Upon the completion of the course, the participants will be able to

  • Utilize the Optimization Toolbox in the MATLAB environment to solve
    optimization problem

  • Write objective function files

  • Add constraints

  • Select appropriate solver and algorithm

  • Interpret the output from solver

  • Increase accuracy



Techsource Systems is
Mathworks Sole and Authorised Distributor and Training Partner

Upcoming Program

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Course Outline

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