A high performance memetic algorithm for extremely high-dimensional problems.

Throughout the last years, optimization problems on a large number of variables, sometimes over 1000, are becoming common. Thus, algorithms that can tackle them effectively, both in result quality and run time, are necessary. Among these specific algorithms for high-dimensional problems, memetic algorithms, which are the result of the hybridization of an evolutionary algorithm and a local improvement technique, have arisen as very powerful optimization systems for this type of problems. A very effective algorithm of this kind is the MA-SW-Chains algorithm. On the other hand, general purpose computing using Graphics Processing Units (GPUs) has become a very active field because of the high speed-up ratios that can be obtained when applied to problems that exhibit a high degree of data parallelism.