## Optimization Techniques in MATLAB

Learn to use optimization and global optimization techniques in MATLAB to solve problems with many variables

### 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 . Knowledge of linear algebra and multivariate calculus is helpful.

### 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
• Select appropriate solver and algorithm
• Interpret the output from solver
• Increase accuracy

#### Partners

TechSource Systems is MathWorks Authorised Reseller and Training Partner

#### Upcoming Program

• Please keep me posted on the next schedule

## Course Outline

#### 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
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