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ENC
2005
IEEE
14 years 4 months ago
Saving Evaluations in Differential Evolution for Constrained Optimization
Generally, evolutionary algorithms require a large number of evaluations of the objective function in order to obtain a good solution. This paper presents a simple approach to sav...
Efrén Mezura-Montes, Carlos A. Coello Coell...
CEC
2009
IEEE
14 years 5 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...
EVOW
1994
Springer
14 years 2 months ago
Competitive Evolution: A Natural Approach to Operator Selection
One of the main problems in applying evolutionary optimisation methods is the choice of operators and parameter values. This paper propose a competitive evolution method, in which ...
Q. Tuan Pham
CPHYSICS
2007
89views more  CPHYSICS 2007»
13 years 10 months ago
Numerical differentiation of experimental data: local versus global methods
In the context of the analysis of measured data, one is often faced with the task to differentiate data numerically. Typically, this occurs when measured data are concerned or dat...
Karsten Ahnert, Markus Abel
AIR
1998
103views more  AIR 1998»
13 years 10 months ago
Tackling Real-Coded Genetic Algorithms: Operators and Tools for Behavioural Analysis
Abstract. Genetic algorithms play a significant role, as search techniques for handling complex spaces, in many fields such as artificial intelligence, engineering, robotic, etc...
Francisco Herrera, Manuel Lozano, José L. V...