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Development of Hybrid Memetic Algorithm and General Regression Neural Network for Generating Iterated Function System Fractals in Jewelry Design Applications

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Advances in Swarm Intelligence (ICSI 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9712))

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Abstract

This paper proposes a hybrid memetic algorithm and a general regression neural network for generating decorative elements. This tool is aimed to be used in jewelry design applications. Local search used is the greedy hill-climbing algorithm. Decorative elements are represented using iterated function systems (IFS) fractals. The aesthetic evaluation used in the design system is modeled using a general regression neural network with multiple perception feed-forward back propagation network to evaluate aesthetics of generated decorative elements. Although this paper demonstrates the application in jewelry design, the proposed algorithm is applicable to other product designs. The results of this study were compared to the results obtained with a genetic algorithm. This comparison implies that the proposed memetic algorithm can obtain better fitness and more variety, but requires larger amount of computational time than the genetic algorithm. The results prove that the proposed algorithm can be applied in design applications.

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Acknowledgments

The research has been carried out as part of the research projects funded by National Research Council of Thailand and Naresaun University with Contract No. R2559B094. The author would like to gratefully thank all participants for their collaboration in this research. Finally, the author would like to thank Dr. Filip Kielar for correcting the manuscript.

Author information

Authors and Affiliations

  1. iD3 - Industrial Design, Decision and Development Research Unit, Department of Industrial Engineering, Faculty of Engineering, Naresuan University, Phitsanulok, 65000, Thailand

    Somlak Wannarumon Kielarova

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  1. Somlak Wannarumon Kielarova
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Correspondence to Somlak Wannarumon Kielarova .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Xi'an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

  3. Shenzhen University, Shenzhen, China

    Ben Niu

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Kielarova, S.W. (2016). Development of Hybrid Memetic Algorithm and General Regression Neural Network for Generating Iterated Function System Fractals in Jewelry Design Applications. In: Tan, Y., Shi, Y., Niu, B. (eds) Advances in Swarm Intelligence. ICSI 2016. Lecture Notes in Computer Science(), vol 9712. Springer, Cham. https://doi.org/10.1007/978-3-319-41000-5_28

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  • DOI: https://doi.org/10.1007/978-3-319-41000-5_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40999-3

  • Online ISBN: 978-3-319-41000-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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