RT Journal Article
T1 On Meme Self-Adaptation in Spatially-Structured Multimemetic Algorithms
A1 Nogueras, Rafael
A1 Cotta-Porras, Carlos
K1 Resolución de problemas
K1 Algoritmos
AB Multimemetic algorithms (MMAs) are memetic algorithms that explicitly exploit the evolution of memes, i.e., non-genetic expressions of problem-solving strategies. We consider a class of MMAs in which these memes are rewriting rules whose length can be fixed during the run of the algorithm or self-adapt during the search process. We analyze this self-adaptation in the context of spatially-structured MMAs, namely MMAs in which the population is endowed with a certain topology to which interactions (from the point of view of selection and variation operators) are constrained. For the problems considered, it is shown that panmictic (i.e., non-structured) MMAs are more sensitive to this self-adaptation, and that using variable-length memes seems to be a robust strategy throughout different population structures.
YR 2014
FD 2014-09-23
LK http://hdl.handle.net/10630/8069
UL http://hdl.handle.net/10630/8069
LA eng
NO NMA 2014
NO This work is partially supported by MICINN project ANYSELF (TIN2011-28627-C04-01), byJunta de Andaluía project DNEMESIS (P10-TIC-6083) and by Universidad de Málaga, Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 19 ene 2026