Genetic Algorithms

Module Code
BI2004
Module Coordinators
Heinz-Uwe Hobohm
Teachers
Heinz-Uwe Hobohm
Short Description
Knowledge of the strength and particular areas of application of genetic algorithms.
Learning Objectives

Students know intricacies of genetic algorithms and the particular strength of GA's. They know how to optimize parameters like mutation rate, rate of recombination and selection. They know how to program and test GA's.

Contents
Optimization of 01-genomes, knapsack, travelling salesman, ant algorithms.
Duration in Semester
1
Instruction Language
German
Total Effort
6 CrP; an estimated 180 hours, of which approximately 60 are spent in class.
Weekly School Hours
4
Method of Instruction

Lecture 1 SWS, Practical Course 3 SWS

Requirements for the awarding of Credit Points

Examination prerequisite: Control of programming exercise

Examination: Written exam

Evaluation Standard
according to examination regulations (§ 9)
Availability
Yearly
References
  • Melanie Mitchell: An introduction to genetic algorithms
  • David Goldberg: Genetic algorithms
  • David Poli, Langdon, McPhee:: A field guide to genetic programming
  • Kursskript
Prerequisites
Programming skills in a scripting language and an object oriented programming language.