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GECCO
2005
Springer
197views Optimization» more  GECCO 2005»
14 years 1 months ago
Performance assessment of an artificial immune system multiobjective optimizer by two improved metrics
In this study, we introduce two improved assessment metrics of multiobjective optimizers, Nondominated Ratio and Spacing Distribution, and analyze their rationality and validity. ...
Maoguo Gong, Licheng Jiao, Haifeng Du, Ronghua Sha...
CEC
2008
IEEE
14 years 2 months ago
An investigation on evolutionary gradient search for multi-objective optimization
—Evolutionary gradient search is a hybrid algorithm that exploits the complementary features of gradient search and evolutionary algorithm to achieve a level of efficiency and r...
Chi Keong Goh, Yew-Soon Ong, Kay Chen Tan, Eu Jin ...
GECCO
2008
Springer
148views Optimization» more  GECCO 2008»
13 years 8 months ago
Accelerating convergence using rough sets theory for multi-objective optimization problems
We propose the use of rough sets theory to improve the first approximation provided by a multi-objective evolutionary algorithm and retain the nondominated solutions using a new ...
Luis V. Santana-Quintero, Carlos A. Coello Coello
TEC
2002
161views more  TEC 2002»
13 years 7 months ago
A fast and elitist multiobjective genetic algorithm: NSGA-II
Multiobjective evolutionary algorithms (EAs) that use nondominated sorting and sharing have been criticized mainly for their: 1) ( 3) computational complexity (where is the number ...
Kalyanmoy Deb, Samir Agrawal, Amrit Pratap, T. Mey...
TCS
2008
13 years 7 months ago
Comparing evolutionary algorithms to the (1+1)-EA
In this paper, we study the conditions in which the (1+1)-EA compares favorably to other evolutionary algorithms (EAs) in terms of fitness function distribution at given iteration...
Pavel A. Borisovsky, Anton V. Eremeev