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Application of genetic algorithms for optimization of tire pitch sequences

  • Yukio Nakajima
  • Akihiko Abe
Article

Abstract

A simple genetic algorithms (GAs) has been applied to generate the optimum pitch sequence. Though a simple GAs worked properly, there was the problem of the premature convergence. To solve this problem, we introduced the new operator named the growth and combined it with a simple GAs. The growth operator, which is a kind of the hill-climbing technique, has the function to get the local optimum in a small CPU time.

The GA with growth generated better sequence than a simple GAs. The GA with growth was verified not to have the premature convergence even in the smaller population size. The optimum pitch sequence generated by the GA with growth improved the noise performance such as pass-by noise compared with the current pitch sequence.

Key words

tire optimization genetic algorithm pitch sequence 

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Copyright information

© JJIAM Publishing Committee 2000

Authors and Affiliations

  • Yukio Nakajima
    • 1
  • Akihiko Abe
    • 1
  1. 1.Bridgestone CorporationTokyoJapan

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