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Optimization Using Genetic Algorithm in MATLAB

Optimization Using Genetic Algorithm in MATLAB

Optimization Using Genetic Algorithm in MATLAB - 
MATLAB programming basics and GA implementation to solve constrained optimization problems in the field of engineering
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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

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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