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GECCO
2009
Springer
146views Optimization» more  GECCO 2009»
15 years 10 months ago
Using a distance metric to guide PSO algorithms for many-objective optimization
In this paper we propose to use a distance metric based on user-preferences to efficiently find solutions for manyobjective problems. We use a particle swarm optimization (PSO) a...
Upali K. Wickramasinghe, Xiaodong Li
CEC
2011
IEEE
14 years 4 months ago
Effective ranking + speciation = Many-objective optimization
—Multiobjective optimization problems have been widely addressed using evolutionary computation techniques. However, when dealing with more than three conflicting objectives (th...
Mario Garza-Fabre, Gregorio Toscano Pulido, Carlos...
SBRN
2000
IEEE
15 years 8 months ago
Evolutionary Optimization of RBF Networks
One of the main obstacles to the widespread use of artijcial neural networks is the difJiculty of adequately define valuesfor their free parameters. This article discusses how Rad...
Estefane G. M. de Lacerda, Teresa Bernarda Ludermi...
ISDA
2010
IEEE
15 years 2 months ago
Avoiding simplification strategies by introducing multi-objectiveness in real world problems
Abstract--In business analysis, models are sometimes oversimplified. We pragmatically approach many problems with a single financial objective and include monetary values for non-m...
Charlotte J. C. Rietveld, Gijs P. Hendrix, Frank T...
156
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EMO
2005
Springer
194views Optimization» more  EMO 2005»
15 years 9 months ago
An EMO Algorithm Using the Hypervolume Measure as Selection Criterion
Abstract. The hypervolume measure is one of the most frequently applied measures for comparing the results of evolutionary multiobjective optimization algorithms (EMOA). The idea t...
Michael Emmerich, Nicola Beume, Boris Naujoks