Metaheuristic Optimization Techniques with Matlab

Description

This course is your introduction to the world of optimization techniques. If you know Matlab or pythons and want to learn how to find the best solution for any problem then this course is for you.

In this course, we will start with an introduction to the world of optimization then we will take the Breadth First Search and Depth First Search which are very important for path planning. Then we will dive into Simulated Annealing, the genetic algorithm, Particle Swarm Optimization and Ant Colony Optimization. After understanding them all we will see how to use them on Matlab. This is all done with quizzes after each two lectures to test your understanding for each topic and at the end of the course you will get an exam to test how much you understood the course and whether you can use these optimization techniques to solve any problem.

The course is important for anyone who wants to learn optimization and how to find the best solution for any problem. Optimization is very important for some artificial intelligence applications and in autonomous systems so this course will open lots of doors for you in the future. The course is divided into 10 lectures

1) Introduction where you will get to know more about optimization and its different types

2) Deterministic techniques which are BFS and DFS

3) SA

4) GA

5) PSO

6) ACO

7) Matlab for SA

8) Matlab for GA

9) Matlab for ACO

10) Matlab for PSO

11) final Exam of 25 questions

What You Will Learn!

• Different Deterministic and Stochastic Optimization Techniques
• Breadth First Search
• Depth First Search
• Simulated Annealing
• Genetic Algorithm
• Particle Swarm Optimization
• Ant Colony Optimization
• Using these techniques with Matlab

Who Should Attend!

• Everyone who is interested in the field of Optimization and Artificial Intelligence

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