An Effective Algorithm for Tool-Path Airtime Optimization during Leather Cutting

Wei Bo Yang; Yan Wei Zhao; Jing Jie; Wan Liang Wang

doi:10.4028/www.scientific.net/AMR.102-104.373

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 102-104An Effective Algorithm for Tool-Path Airtime...

An Effective Algorithm for Tool-Path Airtime Optimization during Leather Cutting

Abstract:

Tool-path airtime optimization problem during multi-contour processing in leather cutting is regarded as generalized traveling salesman problem. A hybrid intelligence algorithm is proposed. The improved genetic simulated annealing algorithm is applied to optimize cutting path selected arbitrarily firstly, and an optimal contour sequence is founded, then problem is changed into multi- segment map problem solved with dynamic programming algorithm. The algorithm's process and its various parameters are given simultaneously, and its performance is compared with simulated annealing and standard genetic algorithm alone. The results show that the algorithm is more effective.

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Periodical:

Advanced Materials Research (Volumes 102-104)

Pages:

373-377

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.102-104.373

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Online since:

March 2010

Authors:

Wei Bo Yang, Yan Wei Zhao, Jing Jie, Wan Liang Wang

Keywords:

Dynamic Programming Algorithm, Genetic-Simulated Annealing Algorithm, Leather Cutting, Multi-Contour Processing, Path Optimization

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References

[1] G.X. Yu, Y.C. Ding and D.C. Li: Journal of Xi'an Jiaotong University, Vol. 38 (2004), pp.39-42.

Google Scholar

[2] C.G. Wu, Y.C. Liang, H.P. Lee, et al: Physical Review E, Vol. 70 (2004), pp.1-13.

Google Scholar

[3] C.F. Tsail, C.W. Tsai and C.C. Tseng: Information Sciences, Vol. 164 (2004), pp.67-81.

Google Scholar

[4] Kenneth, D.S. Roshan and K.W. Paul: Journal of Manufacturing Systems, Vol. 22 (2002), pp.173-180.

Google Scholar

[5] G.S. JI, W. Wang and Z.C. Chen: Journal of Agricultural Machinery, Vol. 39 (2008), pp.154-158.

Google Scholar

[6] H.F. Guo, H.L. Liu, H.S. Li, et al: Computer Engineering and Applications, Vol. 45 (2009), pp.207-209.

Google Scholar

[7] D. Vladimir and S. Zoran: Informatics and Computer Science, Vol. 102 (1997), pp.105-110.

Google Scholar

[8] Cuneyt Oysu and Zafer Bingul: Artificial Intelligence, Vol. 22 (2009), pp.389-396.

Google Scholar

[9] L.V. Snyder and M.S. Daskin: European Journal of Operational Research, Vol. 174 (2006), pp.38-53.

Google Scholar

[10] W.L. Wang: Production Scheduling Intelligent Algorithm and its Applications (Science Press, 2007).

Google Scholar

[11] L. Wang and D.Z. Zheng: Control Theory and Applications, Vol. 18 (2001), pp.552-554.

Google Scholar

[12] H.C. Gao, B.Q. Feng and L. Zhu: Control and Decision, Vol. 21 (2006), pp.241-247.

Google Scholar