TY - GEN
T1 - Local and global order 3/2 convergence of a surrogate evolutionary algorithm
AU - Auger, Anne
AU - Schoenauer, Marc
AU - Teytaud, Olivier
PY - 2005/1/1
Y1 - 2005/1/1
N2 - A Quasi-Monte-Carlo method based on the computation of a surrogate model of the fitness function is proposed, and its convergence at super-linear rate 3/2 is proved under rather mild assumptions on the fitness function - but assuming that the starting point lies within a small neighborhood of a global maximum. A memetic algorithm is then constructed, that performs both a random exploration of the search space and the exploitation of the best-so-far points using the previous surrogate local algorithm, coupled through selection. Under the same mild hypotheses, the global convergence of the memetic algorithm, at the same 3/2 rate, is proved.
AB - A Quasi-Monte-Carlo method based on the computation of a surrogate model of the fitness function is proposed, and its convergence at super-linear rate 3/2 is proved under rather mild assumptions on the fitness function - but assuming that the starting point lies within a small neighborhood of a global maximum. A memetic algorithm is then constructed, that performs both a random exploration of the search space and the exploitation of the best-so-far points using the previous surrogate local algorithm, coupled through selection. Under the same mild hypotheses, the global convergence of the memetic algorithm, at the same 3/2 rate, is proved.
KW - Algorithms
KW - Theory
UR - https://www.scopus.com/pages/publications/32444437598
U2 - 10.1145/1068009.1068154
DO - 10.1145/1068009.1068154
M3 - Conference contribution
AN - SCOPUS:32444437598
SN - 1595930108
SN - 9781595930101
T3 - GECCO 2005 - Genetic and Evolutionary Computation Conference
SP - 857
EP - 864
BT - GECCO 2005 - Genetic and Evolutionary Computation Conference
PB - Association for Computing Machinery (ACM)
T2 - GECCO 2005 - Genetic and Evolutionary Computation Conference
Y2 - 25 June 2005 through 29 June 2005
ER -