Please use this identifier to cite or link to this item:
http://hdl.handle.net/10773/29855
Title: | Robust inventory theory with perishable products |
Author: | Santos, Marcio Costa Agra, Agostinho Poss, Michael |
Keywords: | Lot-sizing Integer programming Robust optimization Row-and-column generation algorithms |
Issue Date: | Jun-2020 |
Publisher: | Springer |
Abstract: | 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. |
Peer review: | yes |
URI: | http://hdl.handle.net/10773/29855 |
DOI: | 10.1007/s10479-019-03264-5 |
ISSN: | 0254-5330 |
Publisher Version: | https://link.springer.com/article/10.1007%2Fs10479-019-03264-5 |
Appears in Collections: | CIDMA - Artigos DMat - Artigos OGTCG - Artigos |
Files in This Item:
File | Description | Size | Format | |
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AnnalsOperResearch.pdf | Main file | 256.02 kB | Adobe PDF | View/Open |
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