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• W2027427296 abstract "We consider the capacitated lot sizing problem with multiple items, setup time and unrelated parallel machines, and apply Dantzig–Wolfe decomposition to a strong reformulation of the problem. Unlike in the traditional approach where the linking constraints are the capacity constraints, we use the flow constraints, i.e. the demand constraints, as linking constraints. The aim of this approach is to obtain high quality lower bounds. We solve the master problem applying two solution methods that combine Lagrangian relaxation and Dantzig–Wolfe decomposition in a hybrid form. A primal heuristic, based on transfers of production quantities, is used to generate feasible solutions. Computational experiments using data sets from the literature are presented and show that the hybrid methods produce lower bounds of excellent quality and competitive upper bounds, when compared with the bounds produced by other methods from the literature and by a high-performance MIP software." @default.
• W2027427296 created "2016-06-24" @default.
• W2027427296 creator A5021704422 @default.
• W2027427296 creator A5027376129 @default.
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• W2027427296 date "2015-11-01" @default.
• W2027427296 modified "2023-10-18" @default.
• W2027427296 title "Hybrid methods for lot sizing on parallel machines" @default.
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• W2027427296 doi "https://doi.org/10.1016/j.cor.2015.04.015" @default.
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