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SYNTHESE
2008
84views more  SYNTHESE 2008»
15 years 6 months ago
How experimental algorithmics can benefit from Mayo's extensions to Neyman-Pearson theory of testing
Although theoretical results for several algorithms in many application domains were presented during the last decades, not all algorithms can be analyzed fully theoretically. Exp...
Thomas Bartz-Beielstein
CDC
2009
IEEE
217views Control Systems» more  CDC 2009»
15 years 7 months ago
Discrete invasive weed optimization algorithm: application to cooperative multiple task assignment of UAVs
This paper presents a novel discrete population based stochastic optimization algorithm inspired from weed colonization. Its performance in a discrete benchmark, timecost trade-off...
Mohsen Ramezani Ghalenoei, Hossein Hajimirsadeghi,...
AEI
2005
99views more  AEI 2005»
15 years 6 months ago
Comparison among five evolutionary-based optimization algorithms
Evolutionary algorithms (EAs) are stochastic search methods that mimic the natural biological evolution and/or the social behavior of species. Such algorithms have been developed ...
Emad Elbeltagi, Tarek Hegazy, Donald E. Grierson
GECCO
2006
Springer
174views Optimization» more  GECCO 2006»
15 years 10 months ago
On the analysis of the (1+1) memetic algorithm
Memetic algorithms are evolutionary algorithms incorporating local search to increase exploitation. This hybridization has been fruitful in countless applications. However, theory...
Dirk Sudholt
DIS
2006
Springer
15 years 10 months ago
A Novel Framework for Discovering Robust Cluster Results
We propose a novel method, called heterogeneous clustering ensemble (HCE), to generate robust clustering results that combine multiple partitions (clusters) derived from various cl...
Hye-Sung Yoon, Sang-Ho Lee, Sung-Bum Cho, Ju Han K...