Introns for accelerating quasi-macroevolution

Ken Naitoh*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


Computational experiments are performed with the simple genetic algorithm (SGA) for a wide range of intron lengths, crossover rates, mutation rates, and replication rates. The best-adapted species emerges widely with a critical intron length proportional to the overall crossover rate in an environment of discontinuous evolution (quasi-macroevolution). This result coincides with the relation between the intron length and mating rate observed in actual Eukaryotes. On the basis of this knowledge, a method for optimizing the crossover rate in the SGA is proposed for the purpose of accomplishing artificial macroevolution in engineering problems.

Original languageEnglish
Pages (from-to)398-405
Number of pages8
JournalJSME International Journal, Series C: Dynamics, Control, Robotics, Design and Manufacturing
Issue number3
Publication statusPublished - 1998 Sept
Externally publishedYes


  • Artificial Intelligence
  • Introns
  • Optimum Design
  • Probabilistic Method
  • Quasi-Macroevolution
  • Simple Genetic Algorithm

ASJC Scopus subject areas

  • Engineering(all)


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