A note on "Reducing the number of binary variables in cutting stock problems"

Hao Chun Lu; Yu Chien Ko; Yao Huei Huang

doi:10.1007/s11590-012-0598-x

A note on "Reducing the number of binary variables in cutting stock problems"

Hao Chun Lu
, Yu Chien Ko
, Yao Huei Huang^*

^*此作品的通信作者

Fu Jen Catholic University
Chung Hua University
National Yang Ming Chiao Tung University

研究成果: 期刊稿件 › 文章 › 同行評審

4 引文斯高帕斯（Scopus）

摘要

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.

原文	英語
頁（從 - 到）	569-579
頁數	11
期刊	Optimization Letters
卷	8
發行號	2
DOIs	https://doi.org/10.1007/s11590-012-0598-x
出版狀態	已出版 - 02 2014
對外發佈	是

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10.1007/s11590-012-0598-x

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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\}",

year = "2014",

month = feb,

doi = "10.1007/s11590-012-0598-x",

language = "英语",

volume = "8",

pages = "569--579",

journal = "Optimization Letters",

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T1 - A note on "Reducing the number of binary variables in cutting stock problems"

AU - Lu, Hao Chun

AU - Ko, Yu Chien

AU - Huang, Yao Huei

PY - 2014/2

Y1 - 2014/2

N2 - 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.

AB - 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.

KW - Binary variables

KW - Cutting stock problem

KW - Deterministic model

UR - https://www.scopus.com/pages/publications/84893722569

U2 - 10.1007/s11590-012-0598-x

DO - 10.1007/s11590-012-0598-x

M3 - 文章

AN - SCOPUS:84893722569

SN - 1862-4472

VL - 8

SP - 569

EP - 579

JO - Optimization Letters

JF - Optimization Letters

IS - 2

ER -

A note on "Reducing the number of binary variables in cutting stock problems"

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