[3–0, 3 cr.]
This course covers widely used meta-heuristic optimization techniques in computing, such as simulated annealing, Tabu search, genetic algorithms, ant algorithms and de-randomized evolution strategies. Serial as well as parallel algorithms will be studied. Students will develop application projects from a wide range of application areas. The advantages and disadvantages of meta-heuristic search methods are discussed.