Robust possibilistic production planning under temporal demand uncertainty with knowledge on dependencies

Romain Guillaume
Proceedings of the Thirteenth International Symposium on Imprecise Probability: Theories and Applications, PMLR 215:241-248, 2023.

Abstract

In this paper, we deal with production planning problem under temporal demand uncertainty. More precisely, a demand forecasting for a given period could move backward in time or forward in time. We investigate the case where knowledge on dependencies on demand is available. This knowledge is taken into account through a family of copula function. The aim results of the paper are: (a) this approach do not increase the complexity of production planning problem, (b) limit the conservatism of fuzzy robust approach for production planning problem and evaluates more precisely the necessity that the cost of a production plan does not exceed a certain threshold.

Cite this Paper

BibTeX
@InProceedings{pmlr-v215-guillaume23a, title = {Robust possibilistic production planning under temporal demand uncertainty with knowledge on dependencies}, author = {Guillaume, Romain}, booktitle = {Proceedings of the Thirteenth International Symposium on Imprecise Probability: Theories and Applications}, pages = {241--248}, year = {2023}, editor = {Miranda, Enrique and Montes, Ignacio and Quaeghebeur, Erik and Vantaggi, Barbara}, volume = {215}, series = {Proceedings of Machine Learning Research}, month = {11--14 Jul}, publisher = {PMLR}, pdf = {https://proceedings.mlr.press/v215/guillaume23a/guillaume23a.pdf}, url = {https://proceedings.mlr.press/v215/guillaume23a.html}, abstract = {In this paper, we deal with production planning problem under temporal demand uncertainty. More precisely, a demand forecasting for a given period could move backward in time or forward in time. We investigate the case where knowledge on dependencies on demand is available. This knowledge is taken into account through a family of copula function. The aim results of the paper are: (a) this approach do not increase the complexity of production planning problem, (b) limit the conservatism of fuzzy robust approach for production planning problem and evaluates more precisely the necessity that the cost of a production plan does not exceed a certain threshold.} }
Endnote
%0 Conference Paper %T Robust possibilistic production planning under temporal demand uncertainty with knowledge on dependencies %A Romain Guillaume %B Proceedings of the Thirteenth International Symposium on Imprecise Probability: Theories and Applications %C Proceedings of Machine Learning Research %D 2023 %E Enrique Miranda %E Ignacio Montes %E Erik Quaeghebeur %E Barbara Vantaggi %F pmlr-v215-guillaume23a %I PMLR %P 241--248 %U https://proceedings.mlr.press/v215/guillaume23a.html %V 215 %X In this paper, we deal with production planning problem under temporal demand uncertainty. More precisely, a demand forecasting for a given period could move backward in time or forward in time. We investigate the case where knowledge on dependencies on demand is available. This knowledge is taken into account through a family of copula function. The aim results of the paper are: (a) this approach do not increase the complexity of production planning problem, (b) limit the conservatism of fuzzy robust approach for production planning problem and evaluates more precisely the necessity that the cost of a production plan does not exceed a certain threshold.
APA
Guillaume, R.. (2023). Robust possibilistic production planning under temporal demand uncertainty with knowledge on dependencies. Proceedings of the Thirteenth International Symposium on Imprecise Probability: Theories and Applications, in Proceedings of Machine Learning Research 215:241-248 Available from https://proceedings.mlr.press/v215/guillaume23a.html.

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