New Tire Design Procedure Based on Optimization Technique

Nakajima, Yoshikazu; Kamegawa, T.; Abe, Akihiko

doi:10.4271/960997

Cited by 11 publications

(2 citation statements)

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“…Hence, we cannot obtain the optimum by the random search which has been used in the tire industry [4]- [7]. Moreover, the mathematical programming, which is the most popular technique in the optimization, cannot be used for the integer type problem in which the design variable is expressed by integer [10], [11], [8]. Hence, we applied a GAs (genetic algorithms) for the optimization of the pitch sequence.…”

Section: Theory Of Pitch Noisementioning

confidence: 99%

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Application of genetic algorithms for optimization of tire pitch sequences

Nakajima

Abe

2000

Japan J. Indust. Appl. Math.

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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 hillclimbing 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.

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Section: Theory Of Pitch Noisementioning

confidence: 99%

“…In order to solve the problem, a simple genetic algorithms (GAs) was applied for the optimization of the pitch sequence by Nakajima et al [8]. Though the pseudo optimum sequence was obtained by a simple GAs, the large population size and many iteration were necessary for the optimization.…”

Section: Introductionmentioning

confidence: 99%