Universität Wien
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040676 KU Metaheuristics (MA) (2020S)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work
Moodle

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).

Details

max. 30 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Monday 20.04. 15:00 - 18:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Monday 20.04. 18:30 - 20:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 21.04. 13:15 - 14:45 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 21.04. 15:00 - 16:30 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 21.04. 16:45 - 18:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 21.04. 18:30 - 20:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Wednesday 22.04. 13:15 - 16:30 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Monday 04.05. 13:15 - 14:45 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Monday 04.05. 15:00 - 18:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Monday 04.05. 18:30 - 20:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 05.05. 13:15 - 18:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Tuesday 05.05. 18:30 - 20:00 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Wednesday 06.05. 13:15 - 14:45 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Wednesday 06.05. 15:00 - 18:15 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß
  • Wednesday 06.05. 18:30 - 19:50 PC-Seminarraum 1 Oskar-Morgenstern-Platz 1 1.Untergeschoß

Information

Aims, contents and method of the course

Heuristics form an indispensable tool for everyone working in operations management because problems arising from practice are often too hard to solve exactly and heuristics are relatively simple methods that may provide feasible solutions of good quality. The course aims at introducing the main concepts of heuristics solution methods and of the modern metaheuristics paradigms developed in the last decades. The methods will be illustrated on the to solve general problems but uses logistics optimization problems such as the vehicle routing problem as examples of specific implementations. The field of routing is in fact so rich that virtually all published heuristic ideas have been applied to it.

The course is further divided into two parts, each of which first covers general problems and then focuses on routing:
• 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.

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.

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%

Examination topics

Greedy and construction heuristics
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.

Association in the course directory

Last modified: Mo 07.09.2020 15:19