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TSMC
2010
13 years 2 months ago
Multiobjective Optimization of Temporal Processes
Abstract--This paper presents a dynamic predictiveoptimization framework of a nonlinear temporal process. Datamining (DM) and evolutionary strategy algorithms are integrated in the...
Zhe Song, Andrew Kusiak
IIS
2000
13 years 9 months ago
Speeding Up Evolution through Learning: LEM
This paper reports briefly on the development of a new approach to evolutionary computation, called the Learnable Evolution Model or LEM. In contrast to conventional Darwinian-typ...
Ryszard S. Michalski, Guido Cervone, Kenneth A. Ka...
GECCO
2004
Springer
175views Optimization» more  GECCO 2004»
14 years 28 days ago
Enhanced Innovation: A Fusion of Chance Discovery and Evolutionary Computation to Foster Creative Processes and Decision Making
Abstract. Human-based genetic algorithms are powerful tools for organizational modeling. If we enhance them using chance discovery techniques, we obtain an innovative approach for ...
Xavier Llorà, Kei Ohnishi, Ying-Ping Chen, ...
GECCO
2006
Springer
137views Optimization» more  GECCO 2006»
13 years 11 months ago
Inside a predator-prey model for multi-objective optimization: a second study
In this article, new variation operators for evolutionary multiobjective algorithms (EMOA) are proposed. On the basis of a predator-prey model theoretical considerations as well a...
Christian Grimme, Karlheinz Schmitt
CIBCB
2007
IEEE
13 years 9 months ago
Optimization of Bacterial Strains with Variable-Sized Evolutionary Algorithms
—In metabolic engineering it is difficult to identify which set of genetic manipulations will result in a microbial strain that achieves a desired production goal, due to the co...
Miguel Rocha, José P. Pinto, Isabel Rocha, ...