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» A New Crossover Operator for Genetic Algorithms
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GECCO
1999
Springer
126views Optimization» more  GECCO 1999»
13 years 12 months ago
Improving Genetic Algorithms by Search Space Reductions (with Applications to Flow Shop Scheduling)
Crossover operators that preserve common components can also preserve representation level constraints. Consequently, these constraints can be used to beneficially reduce the sea...
Stephen Y. Chen, Stephen F. Smith
ENGL
2007
103views more  ENGL 2007»
13 years 7 months ago
Fault Diagnosis of Manufacturing Processes via Genetic Algorithm Approach
—Instantaneous detection and diagnosis of various faults and break-downs in industrial processes is required to reduce production losses and damage to equipments. A solved knowle...
Stefania Gallova
GECCO
2007
Springer
130views Optimization» more  GECCO 2007»
14 years 1 months ago
Variable discrimination of crossover versus mutation using parameterized modular structure
Recent work has provided functions that can be used to prove a principled distinction between the capabilities of mutation-based and crossover-based algorithms. However, prior fun...
Rob Mills, Richard A. Watson
NMA
2010
13 years 5 months ago
Genetic Algorithms Based Parameter Identification of Yeast Fed-Batch Cultivation
Different kinds of genetic algorithms have been investigated for a parameter identification of a fermentation process. Altogether eight realizations of genetic algorithms have been...
Maria Angelova, Stoyan Tzonkov, Tania Pencheva
CEC
2008
IEEE
14 years 2 months ago
Semantically driven crossover in genetic programming
—Crossover forms one of the core operations in genetic programming and has been the subject of many different investigations. We present a novel technique, based on semantic anal...
Lawrence Beadle, Colin G. Johnson