The Ultimate Beginners Guide to Genetic Algorithms in Python

Genetic algorithms are an important area of ​​Artificial Intelligence responsible for solving complex real world problems. There are several practical applications of this type of algorithm, which can be applied to problem solving in everyday business situations. A classic example is solving the problem of teacher schedule in schools, in which there are different combinations of schedules and classes and the goal is to build the schedule dynamically according to the number of classes and the availability of each teacher.

Other examples are: telecommunications companies can design new optical networks, carriers can better plan the delivery route for goods, investors can choose the best investments; among several others. In this course, you will learn everything you need to enter the world of genetic algorithms. What makes this course unique is that you will learn the basic intuition and especially, the step-by-step implementation without using pre-built libraries.

In other words, we are going to implement genetic algorithms from scratch using Python. If you have never heard about this subject, at the end of the course you will have all the theoretical and practical basis to solve your own problems or the problems of the company you work for. In part 1, we are going to implement a genetic algorithm from scratch to solve a very common problem that is related to transportation of products.

Let's suppose we need to load some products on the truck, but we need to select the most profitable products and also take into account that there is not enough space on the truck to load them all. So, the goal of the genetic algorithm will be to choose the best set of products to maximize the profit of the company. At the end we will integrate our algorithm with a database in MySql, so it will be easier to know how to deal with commercial applications.