Particle Swarm Optimization (PSO) in MATLAB — Video Tutorial

In this video tutorial, implementation of Particle Swarm Optimization (PSO) in MATLAB is discussed in detail. In the first part, theoretical foundations of PSO is briefly reviewed. In the next two parts of this video tutorial, PSO is implemented line-by-line and from scratch, and every line of code is described in detail.

After watching this video tutorial, you will be able to know what is PSO, and how it works, and how you can use it to solve your own optimization problems. Also, you will learn how to implement PSO in MATLAB programming language. If you are familiar with other programming languages, it is easy to translate the MATLAB code and rewrite the PSO code in other programming languages.

The video tutorial is available to watch online, via Yarpiz YouTube Channel, and to download as MP4 files. The instructor of this course is Dr. Mostapha Kalami Heris, PhD of Control and Systems Engineering.

After completing this tutorial, you will learn:

• What is Particle Swarm Optimization (PSO) and how it works
• How to implement PSO in MATLAB from scratch
• How to improve the PSO using Constriction Coefficients
• How to solve optimization problems using PSO

Who this course is for:

• Students working on optimization problems and methods, specially engineering and science students, can use PSO as an optimization tool; so this course can help them to enhance their knowlodge about one of most useful meta-heuristics.
• Anyone who is interested in artifical and computational intelligence will find this course useful.

Requirements

• Optimization, specially intelligent optimization tools
• MATLAB programming

Watch Online

Three parts of this video tutorial are available on YouTube and they are embedded into this page as playlist.

Video Files

Part 1/3: Theoretical Foundations (YouTube or Direct Download as MP4 file)

Part 2/3: Implementation in MATLAB (YouTube or Direct Download as MP4 file)

Part 3/3: Improvements (YouTube or Direct Download as MP4 file)

Also the projects files and lecture notes, are available to download, via following URLs.

More About Particle Swarm Optimization

Particle Swarm Optimization (PSO) is an intelligent optimization algorithm based on the Swarm Intelligence. It is based on a simple mathematical model, developed by Kennedy and Eberhart in 1995, to describe the social behavior of birds and fish. The model relies mostly on the basic principles of self-organization which is used to describe the dynamics of complex systems. PSO utilizes a very simplified model of social behavior to solve the optimization problems, in a cooperative and intelligent framework. PSO is one of the most useful and famous metaheuristics and it is successfully applied to various optimization problems.

Downloads

The download links of this project are listed below.

Citing This Work

If you wish, you can cite this content as follows.