Paula Terán-Viadero, Antonio Alonso-Ayuso, F. Javier Martín-Campo
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引用次数: 0
Abstract
AbstractThis paper introduces novel mathematical optimisation models for the 2-Dimensional guillotine Cutting Stock Problem with Variable-Sized Stock that appears in a Spanish company in the honeycomb cardboard industry. This problem mainly differs from the classical cutting stock problems in the stock, which is considered variable-sized, i.e. we have to decide the panel dimensions, width, and length. This approach is helpful in industries where the stock is produced simultaneously with the cutting process. The stock is then cut into smaller rectangular pieces that must meet the customers' requirements, such as the type of item, dimensions, demands, and technical specifications. Furthermore, in the problem tackled in this paper, the cuts are guillotine, performed side to side. The proposed mathematical models are validated using real data from the company, obtaining results that drastically reduce the produced material and leftovers, reducing operation times and economic costs.Keywords: Cutting stock problem2-dimensional cuttingvariable-sized stockmixed integer linear optimisationcardboard industry AcknowledgmentsThe authors would like to thank the company managers for providing us with real data and for giving us insight into the company's current operation.Data availability statementDue to the nature of the research, due to commercial supporting not all data is available. We refer the readers to Terán-Viadero, Alonso-Ayuso, and Martín-Campo (Citation2023) where for six instances, input data and results obtained are reported.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work has been supported by grant PID2021-122640OB-I00 funded by MCIN/AEI/10.13039/501100011033 and by ‘ERDF A way of making Europe’.Notes on contributorsPaula Terán-ViaderoPaula Terán-Viadero is a PhD student who received her Master's degree in 2019 in Mathematical Engineering from the Complutense University of Madrid (UCM), Spain. She specialised in operations research in 2019 when she was part of the Statistics and Operational Research department in the Faculty of Mathematical Sciences at UCM, developing optimisation models for a company in the hospitality sector. Since then, she has worked in the private sector, developing integer linear mathematical optimisation models to solve problems arising from real-world applications.Antonio Alonso-AyusoAntonio Alonso-Ayuso received his PhD in Mathematics from the Complutense University of Madrid, Spain, in 1997. He is currently a Full Professor in Statistics and Operational Research at Rey Juan Carlos University, Spain. His main research interests include linear and integer mathematical optimisation, decision models, and stochastic optimisation applied to combinatorial problems. He has developed several projects jointly with companies in different sectors (steel, oil and paper, among others).F. Javier Martín-CampoF. Javier Martín-Campo received his PhD from the Rey Juan Carlos University, Spain, in 2010. He is currently an Associate Professor in Statistics and Operational Research at Complutense University of Madrid, Spain. His main research interests include Operational Research, particularly Mathematical Programming (Integer, Nonlinear), Decision Aid Models for commercial and humanitarian logistics and heuristics/metaheuristics. He has worked on several projects for different sectors: air traffic management, steel, and paper, among others.
摘要针对西班牙某公司蜂窝纸板工业中出现的变料大小的二维切料问题,介绍了新的数学优化模型。这一问题主要不同于传统的裁切料问题,裁切料被认为是可变尺寸的,即我们必须决定面板的尺寸、宽度和长度。这种方法在库存与切割过程同时生产的行业中是有用的。然后,库存被切成更小的矩形块,这些矩形块必须满足客户的要求,比如产品的类型、尺寸、需求和技术规格。此外,在本文处理的问题中,切割是断头台式的,从一边到另一边进行。利用该公司的实际数据验证了所提出的数学模型,得到的结果大大减少了生产材料和剩余物,减少了操作时间和经济成本。关键词:切料问题二维切料可变大小库存混合整数线性优化纸板行业致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢数据可用性声明由于研究的性质,由于商业支持,并非所有数据都可用。我们建议读者参阅Terán-Viadero、Alonso-Ayuso和Martín-Campo (Citation2023),其中报告了六个实例的输入数据和获得的结果。披露声明作者未报告潜在的利益冲突。本研究由MCIN/AEI/10.13039/501100011033资助的PID2021-122640OB-I00基金和“ERDF A way of making Europe”资助。spula Terán-ViaderoPaula Terán-Viadero是一名博士生,于2019年获得西班牙马德里康普顿斯大学(UCM)数学工程硕士学位。她于2019年专注于运筹学,当时她是UCM数学科学学院统计与运筹学部门的一员,为酒店业的一家公司开发优化模型。此后,她一直在私营部门工作,开发整数线性数学优化模型,以解决现实应用中出现的问题。Antonio Alonso-Ayuso于1997年获得西班牙马德里康普顿斯大学数学博士学位。他目前是西班牙雷胡安卡洛斯大学统计学和运筹学的全职教授。他的主要研究兴趣包括线性和整数数学优化、决策模型和应用于组合问题的随机优化。他与不同行业的公司(钢铁、石油和造纸等)合作开发了几个项目。哈维尔Martin-CampoF。Javier Martín-Campo于2010年获得西班牙雷伊胡安卡洛斯大学博士学位。他目前是西班牙马德里康普顿斯大学统计与运筹学副教授。他的主要研究兴趣包括运筹学,特别是数学规划(整数,非线性),商业和人道主义物流的决策援助模型以及启发式/元启发式。他曾参与多个不同领域的项目:空中交通管理、钢铁和造纸等。
期刊介绍:
The International Journal of Production Research (IJPR), published since 1961, is a well-established, highly successful and leading journal reporting manufacturing, production and operations management research.
IJPR is published 24 times a year and includes papers on innovation management, design of products, manufacturing processes, production and logistics systems. Production economics, the essential behaviour of production resources and systems as well as the complex decision problems that arise in design, management and control of production and logistics systems are considered.
IJPR is a journal for researchers and professors in mechanical engineering, industrial and systems engineering, operations research and management science, and business. It is also an informative reference for industrial managers looking to improve the efficiency and effectiveness of their production systems.