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CEC
2009
IEEE
15 years 10 months ago
Differential Evolution with Laplace mutation operator
— Differential Evolution (DE) is a novel evolutionary approach capable of handling non-differentiable, non-linear and multi-modal objective functions. DE has been consistently ra...
Millie Pant, Radha Thangaraj, Ajith Abraham, Crina...
138
Voted
GECCO
2007
Springer
155views Optimization» more  GECCO 2007»
15 years 10 months ago
Differential evolution and non-separability: using selective pressure to focus search
Recent results show that the Differential Evolution algorithm has significant difficulty on functions that are not linearly separable. On such functions, the algorithm must rely...
Andrew M. Sutton, Monte Lunacek, L. Darrell Whitle...
128
Voted
GECCO
2007
Springer
184views Optimization» more  GECCO 2007»
15 years 10 months ago
Experimental analysis of binary differential evolution in dynamic environments
Many real-world optimization problems are dynamic in nature. The interest in the Evolutionary Algorithms (EAs) community in applying EA variants to dynamic optimization problems h...
Alp Emre Kanlikilicer, Ali Keles, Sima Uyar
126
Voted
CEC
2009
IEEE
15 years 10 months ago
An evaluation of Differential Evolution in software test data generation
— One of the main tasks software testing involves is the generation of the test inputs to be used during the test. Due to its expensive cost, the automation of this task has beco...
Ricardo Landa Becerra, Ramón Sagarna, Xin Y...
175
Voted
GECCO
2010
Springer
197views Optimization» more  GECCO 2010»
15 years 8 months ago
Adaptive strategy selection in differential evolution
Differential evolution (DE) is a simple yet powerful evolutionary algorithm for global numerical optimization. Different strategies have been proposed for the offspring generation...
Wenyin Gong, Álvaro Fialho, Zhihua Cai