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Optimization Using Genetic Algorithm in MATLAB
Rating: 4.2 out of 5(189 ratings)
1,533 students

Optimization Using Genetic Algorithm in MATLAB

MATLAB programming basics and GA implementation to solve constrained optimization problems in the field of engineering
Created byMayank Dadge, Dr. H. T. Jadhav
Last updated 7/2022
English

What you'll learn

  • Write MATLAB program to solve Engineering problems
  • Understand the workings of Genetic Algorithm
  • Implement Genetic Algorithm to solve benchmark functions
  • Implement Genetic Algorithm to solve an engineering optimization problems
  • Design and develop MATLAB program using GA for an engineering optimization problems
  • Work on research problem leading to publication in international journals of high repute

Course content

4 sections • 30 lectures • 2h 38m total length

  • Introduction to MATLAB2:15

    Learn MATLAB basics, including its numerical computation and visualization use, Matrix Laboratory abbreviation, built-in functions and toolboxes, and the interface elements: menu bar, editor, command window, workspace, folders.

  • Variables and Operators6:46
  • Vector Declaration8:35

    Learn to declare vectors in MATLAB by constructing one-by-three and three-by-one matrices with brackets, spaces, commas, or semicolons; use colon, linspace, and transpose to manipulate vector layouts.

  • Indexing and Size of Vectors5:06
  • Matrix Operations7:20

    Explore matrix operations in MATLAB, including scalar operations on vectors, matrix addition and subtraction, matrix multiplication rules, and element-wise operations with dot notation.

  • max(), min(), ones(), and zeros()4:22
  • rand(), randi(), and repmat()3:19
  • If Statement3:17
  • For Loop5:45

    Learn how to use for loops in MATLAB to repeat actions efficiently, including basic syntax, summation of numbers, and nested loops for matrices.

  • While Loop4:17
  • Functions6:59
  • Plots3:55

Requirements

  • Knowledge of basic mathematics

Description

This course is specifically developed for B. Tech. and M. Tech/MS students of all Engineering disciplines. Especially the students of Mechanical, Electrical, Automobile, Chemical, Aeronautical, Electronics, Computer science, Instrumentation, Mechatronics, Manufacturing, Robotics and Civil Engineering can learn MATLAB basics and solve Engineering Optimization problems in their area as part of mini-project or capstone project. In addition to this, the course is also useful to Ph. D. students of different engineering branches. The course is designed in such a way that the student who is not well versed with MATLAB programing can learn the basics of MATLAB in the first part so that it is easy for him/her to understand MATLAB implementation of Genetic Algorithm to solve simple and advanced Engineering problems. The content is so organized that the learner should be able to understand Engineering optimization from scratch and solve research problems leading to publication in an international journal of high repute. It should be useful to students of all universities around the world. 

This course is divided into FOUR Parts

  • Part I - Basics of MATLAB Programming

  • Part 2 - Concept of Genetic Algorithm

  • Part 3 - MATLAB Implementation of GA to solve benchmark functions

  • Part 4 - Capstone Project (MATLAB Implementation of GA to solve a typical Engineering optimization Problem)

Who this course is for:

  • Undergraduate, Post graduate Students and PhD scholars of all Engineering disciplines

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