Sequential Cutting Plane Algorithm

Still, Claus; Westerlund, Tapio

doi:10.1007/978-0-387-74759-0_596

Cited by 1 publication

(1 citation statement)

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“…Third, a nonconvex cutting stock problem can be transformed into a linear or nonlinear mixed integer programming problem by various decomposition techniques. Globally optimal solution of the transformed problem can be then solved by a suitable optimization algorithm such as Branch and Cut for linear problems, or cutting plane methods, − simplicial approximation or conic scalarization for nonlinear ones. Decomposition techniques have been applied, for example, in the solution of a cutting stock problem in corrugated board box industry …”

Section: Introductionmentioning

confidence: 99%

Large Scale Production Planning in the Stainless Steel Industry

Karelahti¹,

Vainiomäki²,

Westerlund

2011

Ind. Eng. Chem. Res.

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We introduce a new formulation for a cutting stock problem in the stainless steel industry. The formulation extends some previous models developed for the paper industry. In this formulation, mother coils are assumed to have finite lengths, and the widths and lengths of the mother coils are considered variables as well as the lengths of the product coils along with the cutting patterns to be used. To enable reuse of scrap material, the trim loss at the end of a mother coil is preferred and collected into a single coil. Finally, the scattering of an order to multiple mother coils is minimized to facilitate the shipping of the order in a single batch. For numerical solution, the inherently nonlinear problem is transformed to a linear one by a decomposition technique. The procedure is illustrated with numerical examples. The presented model has been successfully utilized in large scale industrial environment as a part of the production planning system developed for Outokumpu Stainless by Accenture.

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