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GECCO
2008
Springer
141views Optimization» more  GECCO 2008»
15 years 22 days ago
Potential fitness for genetic programming
We introduce potential fitness, a variant of fitness function that operates in the space of schemata and is applicable to tree-based genetic programing. The proposed evaluation ...
Krzysztof Krawiec, PrzemysBaw Polewski
TEC
2010
121views more  TEC 2010»
14 years 6 months ago
Brain-Computer Evolutionary Multiobjective Optimization: A Genetic Algorithm Adapting to the Decision Maker
The centrality of the decision maker (DM) is widely recognized in the multiple criteria decision-making community. This translates into emphasis on seamless human
Roberto Battiti, Andrea Passerini
GECCO
2000
Springer
121views Optimization» more  GECCO 2000»
15 years 3 months ago
Metaphor for learning: an evolutionary algorithm
The organizational algorithm is examined as a computational approach to representing interpersonal learning. The structure of the algorithm is introduced and described in context ...
Jody Lee Louse, Alexander Kain, James Hines
94
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SAC
2008
ACM
14 years 11 months ago
Dynamic populations in genetic algorithms
Biological populations are dynamic in both space and time, that is, the population size of a species fluctuates across their habitats over time. There are rarely any static or fix...
Zhanshan (Sam) Ma, Axel W. Krings
EOR
2002
125views more  EOR 2002»
14 years 11 months ago
Genetic local search for multi-objective combinatorial optimization
The paper presents a new genetic local search algorithm for multi-objective combinatorial optimization. The goal of the algorithm is to generate in a short time a set of approxima...
Andrzej Jaszkiewicz