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» Combining genetic algorithms with squeaky-wheel optimization
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HIS
2008
13 years 9 months ago
Hybrid Approach for Machine Scheduling Optimization in Custom Furniture Industry
Machine scheduling is a critical problem in industries where products are custom-designed. The wide range of products, the lack of previous experiences in manufacturing, and the s...
Juan Carlos Vidal, Manuel Mucientes, Alberto Bugar...
GECCO
2005
Springer
153views Optimization» more  GECCO 2005»
14 years 1 months ago
Evolving neural network ensembles for control problems
In neuroevolution, a genetic algorithm is used to evolve a neural network to perform a particular task. The standard approach is to evolve a population over a number of generation...
David Pardoe, Michael S. Ryoo, Risto Miikkulainen
WEBI
2005
Springer
14 years 1 months ago
Measuring the Relative Performance of Schema Matchers
Schema matching is a complex process focusing on matching between concepts describing the data in heterogeneous data sources. There is a shift from manual schema matching, done by...
Shlomo Berkovsky, Yaniv Eytani, Avigdor Gal
GECCO
2009
Springer
103views Optimization» more  GECCO 2009»
14 years 2 months ago
Why evolution is not a good paradigm for program induction: a critique of genetic programming
We revisit the roots of Genetic Programming (i.e. Natural Evolution), and conclude that the mechanisms of the process of evolution (i.e. selection, inheritance and variation) are ...
John R. Woodward, Ruibin Bai
JCM
2006
118views more  JCM 2006»
13 years 7 months ago
Joint Optimization of Local and Fusion Rules in a Decentralized Sensor Network
Decentralized sensor networks are collections of individual local sensors that observe a common phenomenon, quantize their observations, and send this quantized information to a ce...
Nithya Gnanapandithan, Balasubramaniam Natarajan