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An optimizing model to solve the nesting problem of rectangle pieces based on genetic algorithm

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Abstract

In the process of cement equipment manufacturing, the demand of rectangle pieces of steel structure is very large. The traditional manual nesting, which is simply cutting by hand-making according to the arrangement of the number and size, causes the low efficiency and material wasting. To solve the problem above, this paper proposes an optimizing model for nesting problem of rectangle pieces. Firstly, with the aim of the maximum utilization ratio of the sheet, the optimization mathematical model for nesting problem of rectangle pieces is established. The lowest horizontal line searching algorithm is described in detail. Secondly, the mathematical model is solved to get the optimal solution by the combination of genetic algorithm and the lowest horizontal line searching algorithm. In the solution process, this paper presents the methods of gene encoding and decoding, definition of fitness function, the design of genetic operators and the design of algorithm operating parameters. Finally, we use one sheet as an example to illustrate the proposed model and algorithm process. Experimental results have shown that the proposed approach is able to achieve rectangle pieces nesting with the maximum material utilization ratio.

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Acknowledgments

This research was financially supported by Project supported by the National Nature Science Fund Project, China (NO. 71171154), the Fundamental Research Funds for the Central Universities (2013-YB-021, 2014-IV-016).

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Authors and Affiliations

  1. Hubei Digital Manufacturing Key Laboratory, School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, 430070, China

    Hongtao Tang, Xixing Li, Shunsheng Guo, Shuwei Liu, Li Li & Lang Huang

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  1. Hongtao Tang
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  2. Xixing Li
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  3. Shunsheng Guo
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  4. Shuwei Liu
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  5. Li Li
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  6. Lang Huang
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Correspondence to Xixing Li.

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Tang, H., Li, X., Guo, S. et al. An optimizing model to solve the nesting problem of rectangle pieces based on genetic algorithm. J Intell Manuf 28, 1817–1826 (2017). https://doi.org/10.1007/s10845-015-1067-z

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  • DOI: https://doi.org/10.1007/s10845-015-1067-z

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