Evolutionary Computation and its Applications

Overview

One of the most important applications of AI in engineering is optimization. Optimization is almost needed everywhere in science and engineering. Compared with traditional mathematical optimization techniques, evolutionary computation, which is a branch of AI, is attracting much attention. After taking this course, students will be able to understand how evolutionary computation works and fluently use AI-based optimization techniques to solve engineering optimization problems via MATLAB. This course introduces fundamental concepts in optimization and the working principles of genetic algorithm and particle swarm optimization in a comprehensive and understandable way. Case studies from real-world engineering are provided, making sure students have the ability to apply what they have learned in real practice. In partnership with MathWorks, enrolled students have access to MATLAB for the duration of the course.

Syllabus

Fundamental Concepts in Optimization

One of the most important applications of AI in science and engineering is optimization. This module introduces fundamental concepts in optimization. After learning this module, students will be able to:

Genetic Algorithm

This module introduces genetic algorithm (GA), which is a famous optimization method inspired by the intelligence of the evolution process. After learning this module, students will be able to:

Particle Swarm Optimization

This module introduces particle swarm optimization (PSO). Swarm intelligence has attracted much attention in the AI field and PSO is a renowned global optimization algorithm based on swarm intelligence. After learning this module, students will be able to: