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» On the Brittleness of Evolutionary Algorithms
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CORR
2010
Springer
117views Education» more  CORR 2010»
15 years 6 months ago
Evolution with Drifting Targets
We consider the question of the stability of evolutionary algorithms to gradual changes, or drift, in the target concept. We define an algorithm to be resistant to drift if, for s...
Varun Kanade, Leslie G. Valiant, Jennifer Wortman ...
PPSN
2004
Springer
15 years 11 months ago
Multi-objective Optimisation by Co-operative Co-evolution
This paper presents the integration between a co-operative co-evolutionary genetic algorithm (CCGA) and four evolutionary multiobjective optimisation algorithms (EMOAs): a multi-ob...
Kuntinee Maneeratana, Kittipong Boonlong, Nachol C...
JCB
2002
108views more  JCB 2002»
15 years 6 months ago
Fast and Accurate Phylogeny Reconstruction Algorithms Based on the Minimum-Evolution Principle
This paper investigates the standard ordinary least-squares version 24 and the balanced version 20 of the minimum evolution principle. For the standard version, we provide a greedy...
Richard Desper, Olivier Gascuel
CEC
2008
IEEE
16 years 27 days ago
Mesh dependency of stress-based crossover for structural topology optimization
— This paper presents a genetic algorithm (GA) with a stress-based crossover (SX) operator to obtain a solution without checkerboard patterns for multi-constrained topology optim...
Cuimin Li, Tomoyuki Hiroyasu, Mitsunori Miki
CEC
2008
IEEE
16 years 27 days ago
Crossover operators to control size growth in linear GP and variable length GAs
— In various nuances of evolutionary algorithms it has been observed that variable sized genomes exhibit large degrees of redundancy and corresponding undue growth. This phenomen...
Dominique Chu, Jonathan E. Rowe