Memetic algorithm
Memetic algorithms is a population-based approach for heuristic search in optimization problems. For some problem domains they have been shown to be more efficient than Genetic algorithms. Some researchers view them as Hybrid Genetic Algorithms or Parallel Genetic Algorithms.
Memetic algorithms are the subject of intense scientific research and have been successfully applied to a multitude of real-world problems ranging from the construction of optimal university exam timetables, to the prediction of protein structures and the optimal design of space-craft trajectories.
References
- 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
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