2015
DOI: 10.1590/0101-7438.2015.035.03.0509
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A New Mathematical Model for the Cutting Stock/Leftover Problem

Abstract: This paper addresses the cutting stock/leftover problem (CSLP), which differs from the ordinary cutting stock problem (CSP) by retaining stock leftovers that can be cut in the future to meet new demands. Therefore, leftovers are not considered waste in the current period. A new mathematical model for the CSLP is presented to capture a well-used strategy in the practice of cutting, which consists of partially cutting the objects in stock, and keeping the leftovers to be cut in the next periods. Computational ex… Show more

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Cited by 25 publications
(20 citation statements)
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“…A. C. Cherri et al [31] considered the one-dimensional cutting stock problem with useable leftovers. M. N. Arenales et al [3] presented a new mathematical model for cutting stock problem using leftover which consisted of partially cutting the stocked items and keeping the remnants to be cut in the next periods. All other dimensions were considered straightforward and computational experiments were performed for a one-dimensional case.…”
Section: Literature Reviewmentioning
confidence: 99%
See 1 more Smart Citation
“…A. C. Cherri et al [31] considered the one-dimensional cutting stock problem with useable leftovers. M. N. Arenales et al [3] presented a new mathematical model for cutting stock problem using leftover which consisted of partially cutting the stocked items and keeping the remnants to be cut in the next periods. All other dimensions were considered straightforward and computational experiments were performed for a one-dimensional case.…”
Section: Literature Reviewmentioning
confidence: 99%
“…A one-dimensional approach has been devised and trim loss at the end of the reels is disregarded in the considered problem formulation. The same approach can also be applied in other industries as well, such as steel [1,2] wood, leather, and plastic industry [3].…”
Section: Introductionmentioning
confidence: 99%
“…Only the first 20 instances in each class were solved by the TPBNT to reduce the total computation time. As mentioned previously in the literature review, existing models (Cui and Yang, 2010;Arenales et al, 2015) can be used to solve the 1DCSPUL_BNT by specifying g UL-types as inputs, whereas the TPBNT optimizes the UL-types by explicitly considering the BT constraint. The TPBNT also specifies the UL-types if G g λ = = is used.…”
Section: Considering Bt Constraintmentioning
confidence: 99%
“…Algunos investigaciones que modifican la técnica antes mencionada, se puede ver en [35], [36], [37] , en estos se restringe el número de veces que cualquier tamaño puede aparecer en un patrón de corte, y se basan en una programación lineal de dos fases: en la primera fase, una solución óptima es obtenida para un conjunto limitado de patrones, y en la segunda fase, la solución óptima es encontrada para todos los patrones.…”
Section: Programación Lineal Enteraunclassified