Running races with Fraser's recombination

@article{Fogel2000RunningRW,
  title={Running races with Fraser's recombination},
  author={David B. Fogel and A. S. Fraser},
  journal={Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512)},
  year={2000},
  volume={2},
  pages={1217-1222 vol.2}
}
  • D. Fogel, A. S. Fraser
  • Published 16 July 2000
  • Mathematics
  • Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512)
Several recombination operators have been proposed in evolutionary computation. Standard procedures include one-point, two-point and uniform crossover. Little attention, however, has been given to a recombination operator that preceded each of these, which was offered by A.S. Fraser (1957). Fraser's recombination assigns a variable probability for crossing over between two solutions at each locus. This operator subsumes the three standard forms of crossover. Experiments are conducted on a set… 
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References

SHOWING 1-10 OF 16 REFERENCES
On the Virtues of Parameterized Uniform Crossover
TLDR
This paper attempts to reconcile opposing views of uniform crossover and present a framework for understanding its virtues, as a growing body of experimental evidence suggests otherwise.
Monte Carlo Analyses of Genetic Models
TLDR
A programme has been written for the SILLIAC which simulates the action of selection on a population segregating for six loci, and the initial population was set to contain the gametic types listed in binary notation in Table 1.
Evolutionary programming made faster
TLDR
A "fast EP" (FEP) is proposed which uses a Cauchy instead of Gaussian mutation as the primary search operator and is proposed and tested empirically, showing that IFEP performs better than or as well as the better of FEP and CEP for most benchmark problems tested.
Simulation of biological evolution and machine learning. I. Selection of self-reproducing numeric patterns by data processing machines, effects of hereditary control, mutation type and crossing.
Evolutionary computation: comments on the history and current state
TLDR
The purpose, the general structure, and the working principles of different approaches, including genetic algorithms (GA), evolution strategies (ES), and evolutionary programming (EP) are described by analysis and comparison of their most important constituents (i.e. representations, variation operators, reproduction, and selection mechanism).
Simulation of Genetic Systems by Automatic Digital Computers VI. Epistasis
Simulation, by Monte Carlo methods, of the effect on the genotype of seleotion against phenotypic extremes has shown that selection will lead to fixation of a simple additive genetic system at an…
Adaptation in natural and artificial systems
TLDR
Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI.
Simulation of Genetic Systems by Automatic Digital Computers II. Effects of Linkage on Rates of Advance Under Selection
TLDR
Varying intensities of selection and tightness of linkage are compared, showing that linkage produces no qualitative effect on the rates of advance at values greater than 0·005, i.e. 0·5 per cent.
Simulation of Genetic Systems by Automatic Digital Computers I. Introduction
Methods of setting automatic digital computers to simulate the algebraic aspects of reproduction, segregation, and selection are discussed. The application of these methods to the problem of the…
Simulation of Genetic Systems by Automatic Digital Computers
TLDR
A new approach to analysis of the effect of selection on gene frequencies is described, and the Monte Carlo method permits inclusion of stochastic processes so that results should simulate those in natural or experimental populations.
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