Optimization problems and algorithms

Course details

This is an introductory course to the stochastic optimization problems and algorithms. We will cover the most fundamental concepts in the field of optimization. By the end of this course, you will be able identify and implement the main components of an optimization problem. Optimization problems are different, yet there have mostly similar challenges and difficulties such as constraints, multiple objectives, discrete variables, and noises. This course will show you how to tackle each of these difficulties. Most of the lectures come with coding videos. In such videos, the step-by-step process of implementing the optimization algorithms or problems are presented. We have also a number of quizzes and exercises to practice the theoretical knowledge covered in the lectures. 

Here is the list of topics covered:

• History of optimization  
• Optimization problems 
• Single-objective optimization algoirhtms 
• Particle Swarm Optimization 
• Optimization of problems with constraints 
• Optimization of problems with binary and/or discrete variables 
• Optimization of problems with multiple objectives
• Optimization of problems with uncertainties