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Article Dans Une Revue Annals of Operations Research Année : 2020

Robust inventory theory with perishable products

Résumé

We consider a robust inventory problem where products are perishable with a given shelf life and demands are assumed uncertain and can take any value in a given polytope. Interestingly, considering uncertain demands leads to part of the production being spoiled, a phenomenon that does not appear in the deterministic context. Based on a deterministic model we propose a robust model where the production decisions are first-stage variables and the inventory levels and the spoiled production are recourse variables that can be adjusted to the demand scenario following a FIFO policy. To handle the non-anticipativity constraints related to the FIFO policy, we propose a non-linear reformulation for the robust problem, which is then linearized using classical techniques. We propose a row-and-column generation algorithm to solve the reformulated model to optimality using a decomposition algorithm. Computational tests show that the decomposition approach can solve a set of instances representing different practical situations within reasonable amount of time. Moreover, the robust solutions obtained ensure low losses of production when the worst-case scenarios are materialized.
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Dates et versions

hal-03113661 , version 1 (18-01-2021)

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Marcio Costa Santos, Agostinho Agra, Michael Poss. Robust inventory theory with perishable products. Annals of Operations Research, 2020, 289 (2), pp.473-494. ⟨10.1007/s10479-019-03264-5⟩. ⟨hal-03113661⟩
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