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AE
2005
Springer
15 years 9 months ago
Algorithms (X, sigma, eta): Quasi-random Mutations for Evolution Strategies
Randomization is an efficient tool for global optimization. We here define a method which keeps : – the order 0 of evolutionary algorithms (no gradient) ; – the stochastic as...
Anne Auger, Mohamed Jebalia, Olivier Teytaud
GECCO
2008
Springer
122views Optimization» more  GECCO 2008»
15 years 5 months ago
Optinformatics for schema analysis of binary genetic algorithms
Given the importance of optimization and informatics which are the two broad fields of research, we present an instance of Optinformatics which denotes the specialization of info...
Minh Nghia Le, Yew-Soon Ong, Quang Huy Nguyen 0001
GECCO
2005
Springer
156views Optimization» more  GECCO 2005»
15 years 9 months ago
The blob code is competitive with edge-sets in genetic algorithms for the minimum routing cost spanning tree problem
Among the many codings of spanning trees for evolutionary search are those based on bijections between Pr¨ufer strings—strings of n−2 vertex labels—and spanning trees on th...
Bryant A. Julstrom
EVOW
2010
Springer
15 years 2 months ago
New Genetic Operators in the Fly Algorithm: Application to Medical PET Image Reconstruction
Abstract. This paper presents an evolutionary approach for image reconstruction in positron emission tomography (PET). Our reconstruction method is based on a cooperative coevoluti...
Franck Patrick Vidal, Jean Louchet, Jean-Marie Roc...
SAMOS
2007
Springer
15 years 10 months ago
An Evolutionary Approach to Area-Time Optimization of FPGA designs
—This paper presents a new methodology based on evolutionary multi-objective optimization (EMO) to synthesize multiple complex modules on programmable devices (FPGAs). It starts ...
Fabrizio Ferrandi, Pier Luca Lanzi, Gianluca Paler...