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The Robust Uncapacitated Lot Sizing Model with Uncertainty Range

Dong Li(dong,li***at***sbs.ox.ac.uk)
Dolores Romero Morales(drm.eco***at***cbs.dk)

Abstract: We study robust versions of the uncapacitated lot sizing problem, where the demand is subject to uncertainty. The robust models are guided by three parameters, namely, the total scaled uncertainty budget, the minimum number of periods in which one would like the demand to be protected against uncertainty, and the minimum scaled protection level per period. We solve the proposed models in polynomial time and give numerical results to show their effectiveness. {\color{red}Under various problem scenarios, we show that the models provide a good trade-off between the robustness of the solution, i.e., to what extend the solution is feasible, and the quality of the objective value. In addition, we show that in many scenarios it is sufficient to apply a special case of the proposed model in which only the uncertainty budget is needed.

Keywords: inventory, robustness and sensitivity analysis, lot sizing, uncertainty budget

Category 1: Applications -- OR and Management Sciences (Production and Logistics )

Category 2: Robust Optimization

Category 3: Integer Programming ((Mixed) Integer Linear Programming )

Citation: Said Business School, University of Oxford, Park End Street, Oxford, OX1 1HP, United Kingdom, January 2017

Download: [PDF]

Entry Submitted: 01/07/2017
Entry Accepted: 01/08/2017
Entry Last Modified: 01/07/2017

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