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EUROGP
2003
Springer
119views Optimization» more  EUROGP 2003»
15 years 12 months ago
Maximum Homologous Crossover for Linear Genetic Programming
We introduce a new recombination operator, the Maximum Homologous Crossover for Linear Genetic Programming. In contrast to standard crossover, it attempts to preserve similar struc...
Michael Defoin-Platel, Manuel Clergue, Philippe Co...
GECCO
2010
Springer
249views Optimization» more  GECCO 2010»
15 years 8 months ago
Towards improved dispatching rules for complex shop floor scenarios: a genetic programming approach
Developing dispatching rules for manufacturing systems is a tedious process, which is time- and cost-consuming. Since there is no good general rule for different scenarios and ob...
Torsten Hildebrandt, Jens Heger, Bernd Scholz-Reit...
EUROGP
2008
Springer
135views Optimization» more  EUROGP 2008»
15 years 8 months ago
Using Genetic Programming for Turing Machine Induction
Abstract. Turing machines are playing an increasingly significant role in Computer Science domains such as bioinformatics. Instead of directly formulating a solution to a problem, ...
Amashini Naidoo, Nelishia Pillay
ESWA
2010
105views more  ESWA 2010»
15 years 4 months ago
A numerical comparison between simulated annealing and evolutionary approaches to the cell formation problem
The Cell Formation Problem is a crucial component of a cell production design in a manufacturing system. This problem consists of a set of product parts to be manufactured in a gr...
Andres Pailla, Athila R. Trindade, Victor Parada, ...
GLOBECOM
2010
IEEE
15 years 4 months ago
Sensor Placement for Minimum Exposure in Distributed Active Sensing Networks
Distributed active sensing is a new sensing paradigm, where active sensors and passive sensors are distributed in a field, and collaboratively detect and track the objects. "E...
Na Xia, Khuong Vu, Rong Zheng