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Bio-Inspired Computation & Optimization (in English)
Last Updated: 2026-02-05 14:57:25
Abstract
This lecture focuses on the foundations of bio-inspired computation with an emphasis on their application to optimization. The exercises will be oriented towards the implementation of these concepts to realistic applications.
Objective
Fundamentals of bio-inspired algorithms for modeling and optimization.
Content
Biologically-inspired computation such as evolutionary algorithms and swarm intelligence is becoming increasingly important in face of the complexity of today's demanding applications. Evolutionary Computation is based on the concept of Darwinian evolution, and takes advantage of todays parallel computer architectures to tackle in an automated fashion complex problems for which traditional optimization and modeling techniques encounter difficulties. Applications of this form of computation are found in diverse fields such as robotics, turbomachinery design, nanodevices and computer aided architecture. The goal of this class is to introduce students to the fundamental concepts of evolutionary computation with an emphasis on their application to optimization. Topics include: Evolution Strategies, Genetic Algorithms, Tabu Search, Swarm Intelligence, and Self-Organisation. The exercises will be oriented towards the implementation of these concepts to realistic applications.
Resources
Literature
- Z. Michalewicz and D. Fogel: How to solve it, Modern Heuristics, Springer - Eric Bonabeau, Marco Dorigo, Guy Theraulaz: Swarm Intelligence: From Natural to Artificial Systems
General Information
- Language
- English
- Frequency
- Yearly recurring
Examination
- Type
- session examination
- Mode
- oral 30 minutes
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture | Bio-Inspired Computation & Optimization (in English) |
|
2 h weekly |
| exercise | Bio-Inspired Computation & Optimization (in English) |
|
1 h weekly |