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Artificial bee colony Optimization Algorithm (Using MATLAB)
Rating: 4.7 out of 5(147 ratings)
1,581 students

Artificial bee colony Optimization Algorithm (Using MATLAB)

Solving Engineering Optimization Problems using Artificial Bee Colony Optimization algorithm (MATLAB Implementation)
Created byDr. H. T. Jadhav, Mayank Dadge
Last updated 7/2022
English
English [Auto],

What you'll learn

  • Write MATLAB program to solve Engineering problems
  • Understand Artificial bee colony Optimization Algorithm (ABC)
  • Implement ABC Algorithm to solve benchmark problems
  • Implement ABC Algorithm to solve Mechanical Engineering problems
  • Design and develop MATLAB program using ABC Algorithm for Mechanical Engineering Optimization problem
  • Work on research problem leading to publication in international journals of high repute

Course content

4 sections • 26 lectures • 3h 16m total length

  • Introduction to MATLAB2:15

    Explore the basics of MATLAB, a matrix laboratory for numerical computation and visualization, and navigate its interface—from the menu bar and editor to the command window and workspace.

  • Variables and Operators6:46

    Explore variables and operators in MATLAB, learning how to store values as matrices, follow naming rules, and apply arithmetic and relational operators in scripts and the workspace.

  • Vector Declaration8:35

    Learn how to declare vectors in MATLAB, create row and column vectors, use spaces, commas, and colons, and apply length and linspace for customizable ranges.

  • Indexing and Size of Vectors5:06

    Learn how to index and size vectors in MATLAB, using X(2) and X(end) for single-row vectors and X(2,3) for two-dimensional arrays. Explore size and length to determine rows and columns.

  • Matrix Operations7:20

    Explore MATLAB matrix operations, including scalar operations, matrix addition, subtraction, and both matrix and element-wise multiplication and division, with dimensional rules and practical examples.

  • max(), min(), ones(), and zeros()4:22

    Explore how the max and min functions extract extremes from vectors and matrix columns, and learn to create 3x3 and 4x4 matrices of ones or zeros in MATLAB.

  • rand(), randi(), and repmat()3:19

    Explore MATLAB's rand, randi, and repmat functions to generate random matrices and replicate matrices, including random decimals, random integers, and repeated patterns.

  • If statement3:17

    The lecture explains the if statement to check conditions and act accordingly, using a positive difference between numbers, with if-then syntax and a default zero result.

  • For Loop5:45

    Master for loops, including nested loops, to repeat actions efficiently in MATLAB, iterating from one to seven and turning matrix ones into zeros by row and column indices.

  • While Loop4:17

    Explore the while loop in MATLAB, compare it with for loop, and learn its syntax and iteration through examples that display numbers 1 to 7 and sum 1 to 25.

  • Functions6:59

    Learn how to declare and use functions in MATLAB, including inputs and outputs, naming conventions, and reusable code for computing a vector average with sum and length.

  • Plots3:55

    Learn MATLAB plotting fundamentals using the plot function to graph x versus y, customize line styles, colors, and markers, and use hold on to overlay graphs.

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 Artificial bee colony 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 Optimization and Artificial bee colony optimization Algorithm (ABC)

  • Part 3 - MATLAB Implementation of ABC algorithm to solve benchmark functions

  • Part 4 - MATLAB Implementation of ABC Algorithm 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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