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^*

^*Corresponding author for this work

Research output: Contribution to journal › Journal Article › peer-review

4 Scopus citations

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.

Original language	English
Pages (from-to)	569-579
Number of pages	11
Journal	Optimization Letters
Volume	8
Issue number	2
DOIs	https://doi.org/10.1007/s11590-012-0598-x
State	Published - 02 2014
Externally published	Yes

Keywords

Binary variables
Cutting stock problem
Deterministic model

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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",

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

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AU - Lu, Hao Chun

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AU - Huang, Yao Huei

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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

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ER -

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

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Keywords

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