@article{fbd03cc646634adcb379e966c77be5df,
title = "A note on {"}Reducing the number of binary variables in cutting stock problems{"}",
abstract = "This study proposes a deterministic model to solve the two-dimensional, cutting stock problem (2DCSP) using a much smaller number of binary variables and thereby reducing the complexity of 2DCSP. Expressing a 2DCSP with m stocks and n cutting rectangles requires 2n2 + n(m + 1) binary variables in the traditional model. In contrast, the proposed model uses n2 + n⌈log2 m⌉ binary variables to express the 2DCSP. Experimental results showed that the proposed model is more efficient than the existing model.",
keywords = "Binary variables, Cutting stock problem, Deterministic model",
author = "Lu, {Hao Chun} and Ko, {Yu Chien} and Huang, {Yao Huei}",
note = "Funding Information: Acknowledgments The authors would like to thank the editor and anonymous referee for providing most valuable comments for us to improve the quality of this manuscript. This research was supported by the project granted by ROC NSC 99-2221-E-030-005-and NSC 100-2221-E-030 -009-.",
year = "2014",
month = feb,
doi = "10.1007/s11590-012-0598-x",
language = "English",
volume = "8",
pages = "569--579",
journal = "Optimization Letters",
issn = "1862-4472",
publisher = "Springer Verlag",
number = "2",
}