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GECCO
2008
Springer
172views Optimization» more  GECCO 2008»
13 years 11 months ago
Empirical analysis of a genetic algorithm-based stress test technique
Evolutionary testing denotes the use of evolutionary algorithms, e.g., Genetic Algorithms (GAs), to support various test automation tasks. Since evolutionary algorithms are heuris...
Vahid Garousi
GECCO
2008
Springer
124views Optimization» more  GECCO 2008»
13 years 11 months ago
Introducing MONEDA: scalable multiobjective optimization with a neural estimation of distribution algorithm
In this paper we explore the model–building issue of multiobjective optimization estimation of distribution algorithms. We argue that model–building has some characteristics t...
Luis Martí, Jesús García, Ant...
GECCO
2008
Springer
161views Optimization» more  GECCO 2008»
13 years 11 months ago
Neuro-evolution for a gathering and collective construction task
In this paper we apply three Neuro-Evolution (NE) methods as controller design approaches in a collective behavior task. These NE methods are Enforced Sub-Populations, MultiAgent ...
D. W. F. van Krevelen, Geoff S. Nitschke
GECCO
2008
Springer
363views Optimization» more  GECCO 2008»
13 years 11 months ago
Towards high speed multiobjective evolutionary optimizers
One of the major difficulties when applying Multiobjective Evolutionary Algorithms (MOEA) to real world problems is the large number of objective function evaluations. Approximate...
A. K. M. Khaled Ahsan Talukder
GECCO
2008
Springer
155views Optimization» more  GECCO 2008»
13 years 11 months ago
Towards memoryless model building
Probabilistic model building methods can render difficult problems feasible by identifying and exploiting dependencies. They build a probabilistic model from the statistical prope...
David Iclanzan, Dumitru Dumitrescu