TY - CHAP
T1 - Memetic algorithms in the presence of uncertainties
AU - Tenne, Yoel
PY - 2012
Y1 - 2012
N2 - Memetic Algorithms have proven to be potent optimization frameworks which are capable of handling a wide range of problems. Stemming from the long-standing understating in the optimization community that no single algorithm can effectively accomplish global optimization [940], memetic algorithms combine global and local search components to balance exploration and exploitation [368, 765]: the global search explores the function landscape while the local search refines solutions. In literature the terms memetic algorithms [615, 673] and hybrid algorithms [325] refer to the same global-local framework just described. The merits of memetic algorithms have been demonstrated in numerous publications, [374, 375, 686, 688].
AB - Memetic Algorithms have proven to be potent optimization frameworks which are capable of handling a wide range of problems. Stemming from the long-standing understating in the optimization community that no single algorithm can effectively accomplish global optimization [940], memetic algorithms combine global and local search components to balance exploration and exploitation [368, 765]: the global search explores the function landscape while the local search refines solutions. In literature the terms memetic algorithms [615, 673] and hybrid algorithms [325] refer to the same global-local framework just described. The merits of memetic algorithms have been demonstrated in numerous publications, [374, 375, 686, 688].
UR - https://www.scopus.com/pages/publications/82655181606
U2 - 10.1007/978-3-642-23247-3_14
DO - 10.1007/978-3-642-23247-3_14
M3 - ???researchoutput.researchoutputtypes.contributiontobookanthology.chapter???
AN - SCOPUS:82655181606
SN - 9783642232466
T3 - Studies in Computational Intelligence
SP - 219
EP - 237
BT - Handbook of Memetic Algorithms
A2 - Neri, Ferrante
A2 - Cotta, Carlos
A2 - Moscato, Pablo
ER -