Optimization with Metaheuristics II (R-Module)

Exam number: 6779

Semester: from 2nd semester

Duration of the module: One semester

Form of the module (i.e. obligatory, elective etc.): Elective

Frequency of module offer: Winter semester 2016/2017

Prerequisites: Maximum 15 participants. Successful exam of Optimization with Metaheuristics. More information regarding the organization and the registration can be found on the Chair’s website.

Applicability of module for other study programmes:
Obligatory or elective in other study programmes. For further information check regulations of the study programme.

Person responsible for module: Prof. Dr. Christian Almeder

Name of the professor: Prof. Dr. Christian Almeder

Language of teaching: English

ECTS-Credits (based on the workload): 6

Workload and its composition (self-study, contact time):
Contact time (Lecture, tutorial etc.): 15 h; self-study: 165 h

Contact hours (per week in semester): 1

Methods and duration of examination:
Successful development and implementation of a metaheuristic, testing and summarizing it a seminar paper of 10-15 pages (and a 20-30 min. presentation of the results)

Emphasis of the grade for the final grade: Please check regulations of the study programme

Aim of the module (expected learning outcomes and competencies to be acquired):
Aim of the course is deepening the knowledge in population-based metaheuristic methods. Students will get familiar with basic concepts of population-based evolutionary optimization methods and learn how to apply such methods to practical planning problems.

Contents of the module:
Genetic Algorithms
Memetic Algorithms
Ant Colony Systems
Particle Swarm Optimization

Teaching and learning methods:
Seminar

Special features (e.g. percentage of online-work, practice, guest speaker, etc.):
Lecture notes and additional material are provided online. Presentations of special topics and case-studies by students.

Literature (compulsory reading, recommended literature):
none

Further information:
Registration in Moodle Viadrina required.