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CEC
2007
IEEE
13 years 11 months ago
Non-separable fitness functions for evolutionary shape optimization benchmarking
—Target shape matching can be used as a quick and easy surrogate task when evaluating optimization algorithms intended for computationally expensive tasks, such as turbine blade ...
Tim A. Yates, Thorsten Schnier
TEC
2002
128views more  TEC 2002»
13 years 4 months ago
A framework for evolutionary optimization with approximate fitness functions
It is not unusual that an approximate model is needed for fitness evaluation in evolutionary computation. In this case, the convergence properties of the evolutionary algorithm are...
Yaochu Jin, Markus Olhofer, Bernhard Sendhoff
CEC
2007
IEEE
13 years 6 months ago
A novel general framework for evolutionary optimization: Adaptive fuzzy fitness granulation
— Computational complexity is a major challenge in evolutionary algorithms due to their need for repeated fitness function evaluations. Here, we aim to reduce number of fitness f...
Mohsen Davarynejad, Mohammad R. Akbarzadeh-Totonch...
GECCO
2006
Springer
146views Optimization» more  GECCO 2006»
13 years 8 months ago
Fitness function for finding out robust solutions on time-varying functions
Evolutionary Computations in dynamic/uncertain environments have attracted much attention. Studies regarding this research subjects can be classified into four categories: Noise, ...
Hisashi Handa
CIMCA
2005
IEEE
13 years 10 months ago
A New Evolutionary Algorithm for Determining the Optimal Number of Clusters
Estimating the optimal number of clusters for a dataset is one of the most essential issues in cluster analysis. An improper pre-selection for the number of clusters might easily ...
Wei Lu, Issa Traoré