Heuristic Optimization
Teaching in winter term
The course Heuristic Optimization (lecture + exercise) is delivered following the inverted classroom paradigm. The course is completely online because it is offered within the international collaborations of RWTH. Video recordings of lectures focusing on specific topics are made available here in Moodle. Advanced discussion of the material as well as the chance to ask questions to the lecturer take place in regular lecture online live sessions. The lecture is accompanied by exercise tasks, which students should attempt to solve on their own. Sample solutions will be presented in exercise online live sessions and made available for download later. Questions about both exercises and lectures can also be asked in the forum .
Please note: Recordings and other material will be made available over time and then remain available until the end of the semester. Kick-off and live sessions will not be recorded.
A detailed schedule and recurring Zoom links for the kick-off and all live sessions will be made available in Moodle.
Content
Complexity theory, greedy algorithm, performance valuation, local search, metaheuristic optimization methods, single-solution methods, population-based methods, applying metaheuristic methods for logistic problems, parameter tuning
Profile
| Language: | English |
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Prerequisites: |
Operations Research 1 or similar knowledge helpful |
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Grading: |
100 % exam |
Learning Goals
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understanding the fundamental concepts for the development of good performing metaheuristics
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to understand, apply and adopt the most important metaheuristics (tabu search, variable neighborhood search, genetic algorithms, …) to solve logistic problems
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to conduct appropriate experiments for fine-tuning the parameters of metaheuristics and to evaluate the performance of metaheuristics