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» An evolutionary method for complex-process optimization
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AIR
2002
165views more  AIR 2002»
15 years 6 days ago
Evolutionary Algorithms for Multi-Objective Optimization: Performance Assessments and Comparisons
The rapid advances of evolutionary methods for multi-objective (MO) optimization poses the difficulty of keeping track of the developments in this field as well as selecting an app...
Kay Chen Tan, Tong Heng Lee, Eik Fun Khor
GECCO
2007
Springer
209views Optimization» more  GECCO 2007»
15 years 6 months ago
Guided hyperplane evolutionary algorithm
A new evolutionary technique for multicriteria optimization called Guiding Hyper-plane Evolutionary Algorithm (GHEA) is proposed. The originality of the approach consists in the f...
Corina Rotar, D. Dumitrescu, Rodica Ioana Lung
ICTAI
2009
IEEE
15 years 7 months ago
Evolution Strategies for Constants Optimization in Genetic Programming
Evolutionary computation methods have been used to solve several optimization and learning problems. This paper describes an application of evolutionary computation methods to con...
César Luis Alonso, José Luis Monta&n...
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HIS
2008
15 years 1 months ago
Evaluating Ranking Composition Methods for Multi-Objective Optimization of Knowledge Rules
Most symbolic classifiers aim at building sets of rules with good coverage and precision. While this is suitable for most applications, they tend to neglect other desirable proper...
Rafael Giusti, Gustavo E. A. P. A. Batista, Ronald...
CORR
2010
Springer
152views Education» more  CORR 2010»
15 years 13 days ago
Neuroevolutionary optimization
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
Eva Volná