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GECCO
2005
Springer
126views Optimization» more  GECCO 2005»
15 years 3 months ago
Not all linear functions are equally difficult for the compact genetic algorithm
Estimation of distribution algorithms (EDAs) try to solve an optimization problem by finding a probability distribution focussed around its optima. For this purpose they conduct ...
Stefan Droste
UPP
2004
Springer
15 years 3 months ago
Inverse Design of Cellular Automata by Genetic Algorithms: An Unconventional Programming Paradigm
Evolving solutions rather than computing them certainly represents an unconventional programming approach. The general methodology of evolutionary computation has already been know...
Thomas Bäck, Ron Breukelaar, Lars Willmes
GECCO
2008
Springer
131views Optimization» more  GECCO 2008»
14 years 11 months ago
The study for transportation planning considered the inventory using hybrid genetic algorithm
The transportation planning (TP) is well-known basic network problem. However, for some real-world applications, it is often that the TP model is extended to satisfy other additio...
Shinichiro Ataka, Mitsuo Gen
GECCO
2007
Springer
558views Optimization» more  GECCO 2007»
15 years 4 months ago
A chain-model genetic algorithm for Bayesian network structure learning
Bayesian Networks are today used in various fields and domains due to their inherent ability to deal with uncertainty. Learning Bayesian Networks, however is an NP-Hard task [7]....
Ratiba Kabli, Frank Herrmann, John McCall
GECCO
2005
Springer
110views Optimization» more  GECCO 2005»
15 years 3 months ago
A genetic algorithm encoding for a class of cardinality constraints
A genetic algorithm encoding is proposed which is able to automatically satisfy a class of important cardinality constraints where the set of distinct values of the design variabl...
Helio J. C. Barbosa, Afonso C. C. Lemonge