Course leader: Gino Bertollucci Colherinhas

Home Institution: UniEVANGÉLICA

Course Overview

This is an introductory course to the Genetic Algorithms. We will cover the most fundamental concepts in nature-inspired Artificial Intelligence techniques as applications in engineering optimization. Both beginners and experts in Artificial Intelligence will benefit from this course since it covers the implementation, theory, and application from basics to advanced topics. In recent years, metaheuristic algorithms, as the Genetic Algorithm, are used to solve real-life complex problems arising from different fields such as economics, engineering, politics, and management.

Learning Outcomes

By the end of this course, students should be able to implement genetic algorithms and design optimal engineer problems by identifying their relevant variables and objectives.

Course Content

The main topics of this course are as follows:

• The historical and mathematical survival of fittest adaptation;
• The various types of genetic operators (selection, crossover, mutation, elitism, decimation) with their pros and cons;
• The variants of Genetic Algorithms;
• The applicability of Genetic Algorithms in mathematics and engineering problems

Instructional Method

The course will include lectures, programming lessons, and group projects.

Required Course Materials

• MATLAB (or equivalent) software;
• Optimization engineering papers

Assessment

A theoretical exam and a group project applied to some classical engineering/ mathematic optimization problem are proposed for the evaluation of the course.