Heuristic Optimization

An introduction to the design of metaheuristic algorithms to address hard combinatorial optimization problems is given. After motivating the need for heuristic optimization through a short excursion into problem complexity, simple heuristic techniques like greedy search and local search are introduced. The main part of the fully virtual course concentrates on the most important metaheuristic paradigms and their application to combinatorial optimization problems. Finally, insights into performance analysis and parameter tuning strategies are given.

After taking this course, students are able to (1) understand basic concepts of the development of effective and efficient metaheuristics, (2) understand and implement greedy algorithms, local search algorithms, and the most important metaheuristic paradigms, (3) adapt these algorithms to solve routing problems, and (4) design reasonable numerical experiments to fine-tune the parameters of a metaheuristic and to assess its performance.

Fundamental knowledge in mathematical modeling and Operations Research

Lectures and exercise sessions are given following the inverted classroom paradigm. Video recordings of the lectures focusing on the course topics are made available on Moodle. Advanced discussion of the material as well as the chance to ask questions to the lecturer takes place in regular online lecture live sessions. The lecture is accompanied by exercises. Sample solutions will be presented in online exercise live sessions and made available for download afterward. Questions about both exercises and lectures can additionally be asked and discussed in a forum on Moodle. Additionally, programming exercises in Python are provided to help students deepen their understanding of the course material through self-study.

Please note: The recordings and other materials will be made available over time and then remain available until the end of the semester. The live sessions will not be recorded.

The two-level mutual trust-based quality assurance scheme has been adopted:

• at the university level: RWTH Aachen has applied its internal quality assurance procedures and structures to the proposal of Heuristic Optimization it submitted to ENHANCE and to its implementation - the related learning activities,
• at the Alliance level: the body composed of Education Officers has made decisions regarding the inclusion of Heuristic Optimization proposed by RWTH Aachen to the Innovative Learning Campus part of the joint ENHANCE educational offer, based on the compliance with the formal requirements and ENHANCE goals.

There are 7 lectures, 5 exercise sessions. Plus, there will be 1 exam question session before the exam. Exams will be in February, March. Dates will be communicated in due time.

Quizzes via Moodle (quizzes do not give a grade bonus)

Grading system: 100% Exam (Examination in English)

Registration deadlines:

• Winter Semester (October 1 to March 31): Registration open from August 1 to 31

How to register + enroll:

1) Create an account and register at the Incoming Students Online Portal within the above mentioned deadlines. Fill out the form “Application: Non-Exchange Incoming Students” and choose the Program “ENHANCE Virtual Mobility.” Please consult our Guidelines for Registration for step-by-step instructions on how to complete the application based on your selected courses.

2) Upon successful registration, you will receive an Admission Letter and a guideline “How to enroll”.

Required documents:

• Certificate of Enrollment at ENHANCE Partner university *
• Copy of passport

3) Enrolling is only possible with an Admission Letter. Deadlines:

• Winter Semester (October 1 to March 31): Enrollment open from August 1 to September 20

4) After successful enrollment register for your ENHANCE Online Course via RWTHonline.

Please note: RWTH students can regularly register via RWTHonline, but need to check with their examination board, whether recognition is possible.

* If your home university is not part of the ENHANCE Alliance, or your home university does not even have a partnership agreement with RWTH, you may contact the Incoming Student Services Team to inquire whether admission for Virtual Mobility is possible.

For course-content related questions: ho@cl.rwth-aachen.de

Recognition: We recommend checking with your local examination board at your home university, whether recognition is possible.