Comparable Experiments Study on the Embedded Optimization Methodology of Self-Organizing

Abstract:

In the previous research, a novel embedded multi-phase optimization methodology was proposed to solve the NC-hard difficulty of self-organizing system involving the complex correlated constraints, which has been theoretically verified. This paper takes a serial of comparable experiments to demonstrate the efficiency of the previously proposed novel methodology. First, the description of the universal problem is given, based which the mathematic model for the self-organizing system is elected. Second, a detailed example that includes complex correlated relationship is suggested. Finally, the detailed experiments verify the correct of the proposed methodology, which integrates these two sub optimization problems into a searching loop to ensure the feasibility of solution and improve the searching efficiency in the complex correlated system, with the graphics, figures, and tables.

• Periodical: Advanced Materials Research (Volumes 181-182)
• Pages: 744-748
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.181-182.744
• Online since: January 2011
• Authors: Ya Bo Luo, Ming Chun Tang
• Keywords: Combinatorial Optimization Problem, Constraint Satisfaction Problems, NP-Hard Difficulty, Optimization Model

References

[1] Ivers, G. G. Yen: IEEE Congress on Evolutionary Computation Vol. 1 (2007), p.3361.

[2] Sierra María R, Varela Ramiro: Journal of Intelligent Manufacturing (2010).

[3] Naderi B, Ghomi S M T Fatemi, Aminnayeri M: Applied Soft Computing Journal (2010).

[4] M. E. Aydin, T. C. Fogarty: Journal of Intelligent Manufacturing (2004).

[5] E. B. Nababan, A. R. Hamdan, S. Abdullah, M. S. Zakaria: International Symposium on Information Technology, Vol. 1 (2007), p.1.

[6] Luo YaBo, Tang MingChun: Key Engineering Materials, Vols. 439-440 (2010), p.505.