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» Evolutionary multiobjective optimization
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GECCO
2008
Springer
101views Optimization» more  GECCO 2008»
15 years 2 months ago
Technical market indicators optimization using evolutionary algorithms
Pablo Fernández-Blanco, Diego J. Bodas-Sagi...
TNN
1998
76views more  TNN 1998»
15 years 1 months ago
Multiobjective genetic algorithm partitioning for hierarchical learning of high-dimensional pattern spaces: a learning-follows-d
— In this paper, we present a novel approach to partitioning pattern spaces using a multiobjective genetic algorithm for identifying (near-)optimal subspaces for hierarchical lea...
Rajeev Kumar, Peter Rockett
CEC
2008
IEEE
15 years 8 months ago
When to use bit-wise neutrality
—Representation techniques are important issues when designing successful evolutionary algorithms. Within this field the use of neutrality plays an important role. We examine th...
Tobias Friedrich, Frank Neumann
GECCO
2005
Springer
136views Optimization» more  GECCO 2005»
15 years 7 months ago
Multi-chromosomal genetic programming
This paper introduces an evolutionary algorithm which uses multiple chromosomes to evolve solutions to a symbolic regression problem. Inspiration for this algorithm is provided by...
Rachel Cavill, Stephen L. Smith, Andrew M. Tyrrell
GECCO
2003
Springer
160views Optimization» more  GECCO 2003»
15 years 7 months ago
Hybridization of Estimation of Distribution Algorithms with a Repair Method for Solving Constraint Satisfaction Problems
Estimation of Distribution Algorithms (EDAs) are new promising methods in the field of genetic and evolutionary algorithms. In the case of conventional Genetic and Evolutionary Al...
Hisashi Handa