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A Product Configuration Optimization Method Based on Non-Dominated Sorting Genetic Algorithm

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Abstract:

In order to realize the complex product rapid configuration design in the environment of mass configuration (MC), the non-dominated sorting genetic algorithm (NGSA) for product rapid configuration design is proposed in this paper. The model of multi-objective product configuration optimization is established, and hierarchical analysis is made for configuration design. By comparing the similarity and integrity of requirement and instance, the sequence of retrieval instances is given according to the reuse degree, and multi-objective optimization configuration based on NGSA is realized. Finally, the validity and practicability of the method is verified by an instance which is applied in rapid configuration design of the drive module of tuyere puncher.

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Periodical:

Advanced Materials Research (Volume 215)

Pages:

366-372

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.215.366

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Online since:

March 2011

Authors:

W.H. Sun, W.C. Lu, D.Y. Lin

Keywords:

Knowledge Reuse, Multi-Objective Optimization (MOP), Non-Dominated Sorting Genetic Algorithm, Product Configuration

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© 2011 Trans Tech Publications Ltd. All Rights Reserved

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References

[1] S. Daniel, W. Rainer: Intelligent Systems, vol. 13(1998), pp.42-48.

Google Scholar

[2] D.C. Brown: Artificial Intelligent for Engineering Desing, Analysis and Manufacturing, Vol. 12(1998), pp.301-306.

Google Scholar

[3] M. Brugnach, G. Bolte, A, Bradshaw: Ecological Modelling, Vol. 160(2003), pp.63-76.

Google Scholar

[4] J. McDermott, R. Weigel: Arificial Intelligence, Vol. 19(1998), pp.39-88.

Google Scholar

[5] L. Qiu: Journal of Mechanical Engineering, Vol. 46(2010), pp.136-141.

Google Scholar

[6] S. Myung, S. Han: Expert Systems with Applications, Vol. 21(2001), pp.99-107.

Google Scholar

[7] F E. reuder: Constraint Programming, Vol. 131(1992), pp.51-74.

Google Scholar

[8] T. Soinninen, T. Tiihonen, R. Mannisto: Artificial Intelligence for Engineering Design, Vol. 4(1998), pp.357-372.

Google Scholar

[9] Y. Dong, K. Xu: Transportation Research Part E: logistics and Transportation Review, Vol. 38(2002), pp.75-95.

Google Scholar

[10] C.C. Lee, C.W. H: European Journal of Operational Research, Vol. 164(2005), pp.158-172.

Google Scholar

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