Abstract
To solve the problem of versatile sizes and irregular number in cut order planning (COP) for apparel mass customization, the mathematical model was built and optimization method based on probability search was proposed. Several cutting table layout plans were generated randomly with the production constriction. The optimized sizes combination plan was accordingly obtained using probability search algorithm. The optimization method could rapidly get the apparel cutting plan and decrease the number of cutting table.
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Jacobs-Blecha, C., Ammons, J.C., Schutte, A., Smith, T.: Cut order planning for apparel manufacturing. IIE Transactions 30, 79–90 (1998)
Dawn, M.R., Douglas, R.S.: Cut scheduling in the apparel industry. J. Computers & Operations Research 34, 3209–3228 (2006)
Jiang, X.-w.: Research on apparel cut order planning optimization system. Sichuan Silk 12(2), 41–44 (2000)
Sun, X.-y., Qiu, Y.-y.: How to make cut oreder planning in apparel production. China Textile Leader 2, 40–41 (2003)
Bouziri, A., M’Hallah, R.: A Hybrid Genetic Algorithm for the Cut Order Planning Problem. In: Okuno, H.G., Ali, M. (eds.) IEA/AIE 2007. LNCS (LNAI), vol. 4570, pp. 454–463. Springer, Heidelberg (2007)
Wong, W.K., Leung, S.Y.S.: Genetic optimization of fabric utilization in apparel manufacturing. Int. J. Production Economics 114, 376–387 (2008)
Degraeve, Z., Vandebroek, M.: A mixed integer programming model for solving a layout problem in the fashion industry. Management Science 44, 301–310 (1998)
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Yan-mei, L., Shao-cong, Y., Shu-ting, Z. (2011). Research on Cut Order Planning for Apparel Mass Customization. In: Deng, H., Miao, D., Wang, F.L., Lei, J. (eds) Emerging Research in Artificial Intelligence and Computational Intelligence. AICI 2011. Communications in Computer and Information Science, vol 237. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24282-3_36
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DOI: https://doi.org/10.1007/978-3-642-24282-3_36
Publisher Name: Springer, Berlin, Heidelberg
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