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» An evolutionary method for complex-process optimization
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GECCO
2010
Springer
184views Optimization» more  GECCO 2010»
15 years 3 months ago
A mono surrogate for multiobjective optimization
Most surrogate approaches to multi-objective optimization build a surrogate model for each objective. These surrogates can be used inside a classical Evolutionary Multiobjective O...
Ilya Loshchilov, Marc Schoenauer, Michèle S...
117
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GPEM
2002
163views more  GPEM 2002»
15 years 9 days ago
Fast Ant Colony Optimization on Runtime Reconfigurable Processor Arrays
Ant Colony Optimization (ACO) is a metaheuristic used to solve combinatorial optimization problems. As with other metaheuristics, like evolutionary methods, ACO algorithms often sh...
Daniel Merkle, Martin Middendorf
98
Voted
GECCO
2007
Springer
183views Optimization» more  GECCO 2007»
15 years 6 months ago
Self-adaptive simulated binary crossover for real-parameter optimization
Simulated binary crossover (SBX) is a real-parameter recombination operator which is commonly used in the evolutionary algorithm (EA) literature. The operator involves a parameter...
Kalyanmoy Deb, Karthik Sindhya, Tatsuya Okabe
114
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CDC
2009
IEEE
217views Control Systems» more  CDC 2009»
15 years 1 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,...
94
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AEI
2005
99views more  AEI 2005»
15 years 13 days 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