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» On the Brittleness of Evolutionary Algorithms
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EMO
2003
Springer
81views Optimization» more  EMO 2003»
15 years 11 months ago
Solving Hierarchical Optimization Problems Using MOEAs
Abstract. In this paper, we propose an approach for solving hierarchical multi-objective optimization problems (MOPs). In realistic MOPs, two main challenges have to be considered:...
Christian Haubelt, Sanaz Mostaghim, Jürgen Te...
EUROGP
2003
Springer
101views Optimization» more  EUROGP 2003»
15 years 11 months ago
An Enhanced Framework for Microprocessor Test-Program Generation
Test programs are fragment of code, but, unlike ordinary application programs, they are not intended to solve a problem, nor to calculate a function. Instead, they are supposed to ...
Fulvio Corno, Giovanni Squillero
GECCO
2003
Springer
123views Optimization» more  GECCO 2003»
15 years 11 months ago
Analysis of the (1+1) EA for a Dynamically Bitwise Changing OneMax
Abstract. Although evolutionary algorithms (EAs) are often successfully used for the optimization of dynamically changing objective function, there are only very few theoretical re...
Stefan Droste
GECCO
2003
Springer
182views Optimization» more  GECCO 2003»
15 years 11 months ago
Spatial Operators for Evolving Dynamic Bayesian Networks from Spatio-temporal Data
Learning Bayesian networks from data has been studied extensively in the evolutionary algorithm communities [Larranaga96, Wong99]. We have previously explored extending some of the...
Allan Tucker, Xiaohui Liu, David Garway-Heath
GECCO
2003
Springer
115views Optimization» more  GECCO 2003»
15 years 11 months ago
A Specialized Island Model and Its Application in Multiobjective Optimization
This paper discusses a new model of parallel evolutionary algorithms (EAs) called the specialized island model (SIM) that can be used to generate a set of diverse non-dominated sol...
Ningchuan Xiao, Marc P. Armstrong