Macroscopic kinetic equation for a genetic algorithm

研究成果: Article

9 引用 (Scopus)

抄録

A macroscopic kinetic equation of only four variables for a simple genetic algorithm (SGA) with an on-off type of replication operator and a crossover operator is developed and used to predict several types of evolutionary routes for a wide range of metabolic-rate-controlling parameters, initial conditions, string lengths, population sizes, and environments. The four variables correspond to the probabilities of the best-adapted species and three mutant groups into which degenerate and redundant strings are classified according to the Hamming distance (HD). The time-dependent frequency distribution along the fitness value is given by an implicit formulation. The environment is also defined in the HD-fitness value space as the frequency distribution of all the possible types of strings without redundancy. It is found that the SGA possesses the capability for exploring quasi-macroevolution.

元の言語English
ページ(範囲)87-133
ページ数47
ジャーナルJapan Journal of Industrial and Applied Mathematics
15
発行部数1
出版物ステータスPublished - 1998 2
外部発表Yes

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Hamming distance
Kinetic Equation
Strings
Genetic algorithms
Hamming Distance
Genetic Algorithm
Fitness
Kinetics
Redundancy
Crossover Operator
Population Size
Mutant
Replication
Initial conditions
Predict
Formulation
Operator
Range of data

ASJC Scopus subject areas

  • Mathematics(all)
  • Applied Mathematics

これを引用

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