Genetic range genetic algorithms to obtain quasi-optimum solutions

Masao Arakawa, Tomoyuki Miyashita, Hiroshi Ishikawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

In some cases of developing a new product, response surface of an objective function is not always single peaked function, and it is often multi-peaked function. In that case, designers would like to have not only global optimum solution but also as many local optimum solutions and/or quasi-optimum solutions as possible, so that he or she can select one out of them considering the other conditions that are not taken into account priori to optimization. Although this information is quite useful, it is not that easy to obtain with a single trial of optimization. In this study, we will propose a screening of fitness function in genetic algorithms (GA). Which change fitness function during searching. Therefore, GA needs to have higher flexibility in searching. Genetic Range Genetic Algorithms include a number of searching range in a single generation. Just like there are a number of species in wild life. Therefore, it can arrange to have both global searching range and also local searching range with different fitness function. In this paper, we demonstrate the effectiveness of the proposed method through a simple benchmark test problems.

Original languageEnglish
Title of host publicationProceedings of the ASME Design Engineering Technical Conference
Pages927-934
Number of pages8
Volume2 B
Publication statusPublished - 2003
Externally publishedYes
Event2003 ASME Design Engineering Technical Conferences and Computers and Information in Engineering Conference - Chicago, IL
Duration: 2003 Sep 22003 Sep 6

Other

Other2003 ASME Design Engineering Technical Conferences and Computers and Information in Engineering Conference
CityChicago, IL
Period03/9/203/9/6

Fingerprint

Genetic algorithms
Screening

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Arakawa, M., Miyashita, T., & Ishikawa, H. (2003). Genetic range genetic algorithms to obtain quasi-optimum solutions. In Proceedings of the ASME Design Engineering Technical Conference (Vol. 2 B, pp. 927-934)

Genetic range genetic algorithms to obtain quasi-optimum solutions. / Arakawa, Masao; Miyashita, Tomoyuki; Ishikawa, Hiroshi.

Proceedings of the ASME Design Engineering Technical Conference. Vol. 2 B 2003. p. 927-934.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Arakawa, M, Miyashita, T & Ishikawa, H 2003, Genetic range genetic algorithms to obtain quasi-optimum solutions. in Proceedings of the ASME Design Engineering Technical Conference. vol. 2 B, pp. 927-934, 2003 ASME Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Chicago, IL, 03/9/2.
Arakawa M, Miyashita T, Ishikawa H. Genetic range genetic algorithms to obtain quasi-optimum solutions. In Proceedings of the ASME Design Engineering Technical Conference. Vol. 2 B. 2003. p. 927-934
Arakawa, Masao ; Miyashita, Tomoyuki ; Ishikawa, Hiroshi. / Genetic range genetic algorithms to obtain quasi-optimum solutions. Proceedings of the ASME Design Engineering Technical Conference. Vol. 2 B 2003. pp. 927-934
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