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GECCO
2009
Springer
118views Optimization» more  GECCO 2009»
13 years 10 months ago
Benchmarking the pure random search on the BBOB-2009 noisy testbed
We benchmark the Pure-Random-Search algorithm on the BBOB 2009 noisy testbed. Each candidate solution is sampled uniformly in [−5, 5]D , where D denotes the search space dimensi...
Anne Auger, Raymond Ros
GECCO
2009
Springer
148views Optimization» more  GECCO 2009»
13 years 10 months ago
Benchmarking the NEWUOA on the BBOB-2009 noisy testbed
The NEWUOA which belongs to the class of DerivativeFree optimization algorithms is benchmarked on the BBOB2009 noisy testbed. A multistart strategy is applied with a maximum numbe...
Raymond Ros
GECCO
2009
Springer
150views Optimization» more  GECCO 2009»
13 years 10 months ago
Benchmarking a BI-population CMA-ES on the BBOB-2009 function testbed
We propose a multistart CMA-ES with equal budgets for two interlaced restart strategies, one with an increasing population size and one with varying small population sizes. This B...
Nikolaus Hansen
GECCO
2009
Springer
170views Optimization» more  GECCO 2009»
13 years 10 months ago
Benchmarking a BI-population CMA-ES on the BBOB-2009 noisy testbed
We benchmark the BI-population CMA-ES on the BBOB2009 noisy functions testbed. BI-population refers to a multistart strategy with equal budgets for two interlaced restart strategi...
Nikolaus Hansen
GECCO
2009
Springer
151views Optimization» more  GECCO 2009»
13 years 10 months ago
Black-box optimization benchmarking for noiseless function testbed using particle swarm optimization
This paper benchmarks the Particle Swarm Optimization (PSO) algorithm using the noise-free BBOB 2009 testbed. Categories and Subject Descriptors
Mohammed El-Abd, Mohamed S. Kamel