Asymmetrical Evaluation of Forecasting Models Through Fresh Food Product Characteristics - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2019

Asymmetrical Evaluation of Forecasting Models Through Fresh Food Product Characteristics

Résumé

Forecasting accuracy in context of fresh meat products with short shelf life is studied. Main findings are that forecasting accuracy measures (i.e. errors) should penalize deviations differently according to product characteristics, mainly dependent on whether the deviation is large or small, negative or positive. This study proposes a decision-based mean hybrid evaluation which penalize deviations according to type of animal, demand type, product life cycle and product criticality, i.e. shelf life, inventory level and future demand.
Fichier principal
Vignette du fichier
489100_1_En_21_Chapter.pdf (249.91 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-02419236 , version 1 (19-12-2019)

Licence

Paternité

Identifiants

Citer

Flemming Christensen, Iskra Dukovska-Popovska, Casper S. Bojer, Kenn Steger-Jensen. Asymmetrical Evaluation of Forecasting Models Through Fresh Food Product Characteristics. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2019, Austin, TX, United States. pp.155-163, ⟨10.1007/978-3-030-30000-5_21⟩. ⟨hal-02419236⟩
33 Consultations
67 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More