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GECCO
2006
Springer
202views Optimization» more  GECCO 2006»
15 years 1 months ago
Evolving hash functions by means of genetic programming
The design of hash functions by means of evolutionary computation is a relatively new and unexplored problem. In this work, we use Genetic Programming (GP) to evolve robust and fa...
César Estébanez, Julio César ...
GECCO
2006
Springer
137views Optimization» more  GECCO 2006»
15 years 1 months ago
A unified optimization framework for microelectronics industry
In this paper, an object-oriented unified optimization framework (UOF) for general problem optimization is proposed. Based on evolutionary algorithms, numerical deterministic meth...
Yiming Li, Cheng-Kai Chen, Yen-Yu Cho
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GECCO
2006
Springer
133views Optimization» more  GECCO 2006»
15 years 1 months ago
String transformation-based Bayesian classification or proteins
We describe a Markov chain Bayesian classification tool, SCS, that can perform data-driven classification of proteins and protein segments. Training data for interesting classific...
Timothy Meekhof, Gary W. Daughdrill, Robert B. Hec...
GECCO
2006
Springer
167views Optimization» more  GECCO 2006»
15 years 1 months ago
Genomic computing networks learn complex POMDPs
A genomic computing network is a variant of a neural network for which a genome encodes all aspects, both structural and functional, of the network. The genome is evolved by a gen...
David J. Montana, Eric Van Wyk, Marshall Brinn, Jo...
GECCO
2006
Springer
179views Optimization» more  GECCO 2006»
15 years 1 months ago
Comparison of multi-objective evolutionary algorithms in optimizing combinations of reinsurance contracts
Our paper concerns optimal combinations of different types of reinsurance contracts. We introduce a novel approach based on the Mean-Variance-Criterion to solve this task. Two sta...
Ingo Oesterreicher, Andreas Mitschele, Frank Schlo...