TY - GEN
T1 - Benchmarking the nelder-mead downhill simplex algorithm with many local restarts
AU - Hansen, Nikolaus
N1 - Publisher Copyright:
© 2009 ACM.
PY - 2009/1/1
Y1 - 2009/1/1
N2 - We benchmark the Nelder-Mead downhill simplex method on the noisefree BBOB-2009 testbed. A multistart strategy is applied on two levels. On a local level, at least ten restarts are conducted with a small number of iterations and reshaped simplex. On the global level independent restarts are launched until $10^5 D$ function evaluations are exceeded, for dimension $D\ge20$ ten times less. For low search space dimensions the algorithm shows very good results on many functions. It solves 24, 18, 11 and 7 of 24 functions in 2, 5, 10 and 40-D.
AB - We benchmark the Nelder-Mead downhill simplex method on the noisefree BBOB-2009 testbed. A multistart strategy is applied on two levels. On a local level, at least ten restarts are conducted with a small number of iterations and reshaped simplex. On the global level independent restarts are launched until $10^5 D$ function evaluations are exceeded, for dimension $D\ge20$ ten times less. For low search space dimensions the algorithm shows very good results on many functions. It solves 24, 18, 11 and 7 of 24 functions in 2, 5, 10 and 40-D.
KW - Benchmarking
KW - Black-box optimization
KW - Direct search
KW - Evolutionary computation
KW - Simplex downhill
U2 - 10.1145/1570256.1570335
DO - 10.1145/1570256.1570335
M3 - Conference contribution
AN - SCOPUS:85020615863
SN - 9781605583259
T3 - Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009
SP - 2403
EP - 2408
BT - Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009
PB - Association for Computing Machinery
T2 - 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009
Y2 - 8 July 2009 through 12 July 2009
ER -