Memetic algorithm

Memetic algorithms are a population-based approach for heuristic search in optimization problems. For some problems they have proven to be more efficient than pure genetic algorithms. Some researchers regard them as hybrid genetic algorithms or parallel genetic algorithms.

Judging from genetic algorithms and adds local search, this is called a memetic algorithm.

Memetic algorithms have already been applied to a variety of real problems, for example to create a university timetable, for the prediction of protein structures or to calculate trajectories.

Memetics is a research direction are studied in the evolutionary processes that occur in the distribution and modification of ideas and other cultural concepts. These processes can be regarded as a natural model for the described algorithms, hence the term memetic.

Credentials

• P. Moscato, On Evolution, Search, Optimization, Genetic Algorithms and Martial Arts: Towards Memetic Algorithms, Caltech Concurrent Computation Program, C3P Report 826, (1989).
• Recent Advances in Memetic Algorithms, Series: Studies in Fuzziness and Soft Computing, Vol 166, Hart, William E.; Krasnogor, N.; Smith, J. E. (Eds. ), 2005

• Evolutionary algorithm