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GECCO
2008
Springer
141views Optimization» more  GECCO 2008»
13 years 11 months 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»
13 years 4 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»
14 years 1 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
SAC
2008
ACM
13 years 9 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»
13 years 9 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