Methoden und Anwendungen der Optimierung

 

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

Learning objective


After the course, the students are able to

  • understanding the fundamental concepts for the development of good performing metaheuristics
  • to understand, apply and adopt the most important metaheuristics (tabu search, variable neighborhood search, genetic algorithms, …) to solve logistic problems
  • to conduct appropriate experiments for fine-tuning the parameters of metaheuristics and to evaluate the performance of metaheuristics