040676 KU Metaheuristics (MA) (2019W)
Continuous assessment of course work
Labels
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Mo 16.09.2019 09:00 to Mo 23.09.2019 12:00
- Registration is open from Th 26.09.2019 09:00 to Fr 27.09.2019 12:00
- Deregistration possible until Mo 14.10.2019 12:00
Details
max. 30 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Tuesday 14.01. 08:00 - 14:45 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Tuesday 14.01. 15:00 - 16:30 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Wednesday 15.01. 08:00 - 09:30 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Wednesday 15.01. 09:45 - 11:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Wednesday 15.01. 11:30 - 14:45 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Wednesday 15.01. 15:05 - 16:30 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Thursday 16.01. 08:00 - 11:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Thursday 16.01. 11:30 - 14:45 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Tuesday 28.01. 11:30 - 13:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Tuesday 28.01. 13:15 - 14:45 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Tuesday 28.01. 15:00 - 16:30 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Tuesday 28.01. 16:45 - 18:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Wednesday 29.01. 08:00 - 13:10 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Wednesday 29.01. 13:15 - 15:00 PC-Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Untergeschoß
- Wednesday 05.02. 09:45 - 11:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
Information
Aims, contents and method of the course
Assessment and permitted materials
The Assessment of the course will be provided by a written exam covering both methodological open questions and simple exercises on the application and modification of heuristics. No programming is included in the exam.
Given the methodological content of the exam, lecture notes and other books are not permitted during the exam.
During the course will be discussed with the students the possibility of having a homework assignment. In case the homework assignment is defined it will amount 20% of the final grade and the written exam 80%, otherwise the written exam will account for 100% of the final grade.
Given the methodological content of the exam, lecture notes and other books are not permitted during the exam.
During the course will be discussed with the students the possibility of having a homework assignment. In case the homework assignment is defined it will amount 20% of the final grade and the written exam 80%, otherwise the written exam will account for 100% of the final grade.
Minimum requirements and assessment criteria
Appropriate points will be assigned to each part of the exam and to the possible homework, the grading will be scaled in 100%.
In order to pass the course (minimum requirement) students have to achieve at least 50% in total.The other grades are distributed as follows:
4: 50% to <63%
3: 63% to <75%
2: 75% to <87%
1: 87% to 100%
In order to pass the course (minimum requirement) students have to achieve at least 50% in total.The other grades are distributed as follows:
4: 50% to <63%
3: 63% to <75%
2: 75% to <87%
1: 87% to 100%
Examination topics
Greedy and construction heuristics
Local search improvement methods
Metaheuristics (evolutionary and local search based)
Local search improvement methods
Metaheuristics (evolutionary and local search based)
Reading list
Lecture notes and coding companion available online.
Selection of chapters from these books:
• Michalewicz, Z. and Fogel, D.B. (2004). How to solve it: modern heuristics. Springer
• Talbi, El-Ghazali (2009). Metaheuristics: From Design to Implementation. Wiley
• Toth, P. and Vigo, D. (2002). The Vehicle Routing Problem, 1st edition. SIAM.
• Toth, P. and Vigo, D. (2014). Vehicle Routing: Problems, Methods and Applications, 2nd edition. SIAM.
Selection of chapters from these books:
• Michalewicz, Z. and Fogel, D.B. (2004). How to solve it: modern heuristics. Springer
• Talbi, El-Ghazali (2009). Metaheuristics: From Design to Implementation. Wiley
• Toth, P. and Vigo, D. (2002). The Vehicle Routing Problem, 1st edition. SIAM.
• Toth, P. and Vigo, D. (2014). Vehicle Routing: Problems, Methods and Applications, 2nd edition. SIAM.
Association in the course directory
Last modified: Mo 07.09.2020 15:19
• Classical heuristics to construct a feasible solution and improvement heuristics based on structured local search
• Metaheuristics aiming at escaping local optima
All methods will be illustrated through actual implementations in high level language.
By the end of the course students will be able to:
- Identify problems which will require heuristics for their solution.
- Identify the appropriate heuristic for the solution of a problem.
- Discuss the characteristics of the main heurisitc and metaheuristic techniques by considering their efficiency and effectiveness.
- Develop implementations of heuristics for optimization and vehicle routing problems.