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• W2061717788 abstract "The cutting stock problem (CSP) is one of the most fascinating problems in operations research. The problem aims at determining the optimal plan to cut a number of parts of various length from an inventory of standard-size material so to satisfy the customers demands. The deterministic CSP ignores the uncertain nature of the demands thus typically providing recommendations that may result in overproduction or in profit loss. This paper proposes a stochastic version of the CSP which explicitly takes into account uncertainty. Using a scenario-based approach, we develop a two-stage stochastic programming formulation. The highly non-convex nature of the model together with its huge size prevent the application of standard software. We use a solution approach designed to exploit the specific problem structure. Encouraging preliminary computational results are provided." @default.
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• W2061717788 date "2009-08-01" @default.
• W2061717788 modified "2023-10-14" @default.
• W2061717788 title "The stochastic trim-loss problem" @default.
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• W2061717788 doi "https://doi.org/10.1016/j.ejor.2008.04.042" @default.
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