Machine learning and observation-driven models in inventory forecasting under fill rate constraints
2019/35/O/HS4/00345
Keywords
Descriptors
- HS4_003: Ekonometria i metody statystyczne
- ST8_011: Planowanie i sterowanie produkcją
- HS4_009: Zarządzanie organizacjami, zarządzanie strategiczne, koncepcje i metody zarządzania, logistyka
Panel
HS4 – Individuals, institutions, markets: economics, finance, management, demography, social and economic geography, urban studies
Host institution
Uniwersytet Mikołaja Kopernika, Wydział Nauk Ekonomicznych i Zarządzania
Voivodeship: kujawsko-pomorskie
Principal investigator (from the host institution)
Number of co-investigators in the project: 2
Call
PRELUDIUM BIS 1 – announced on 2019-09-16
- Amount awarded
- 436 800 PLN
- Project start date
- 2020-10-01
- Project end date
- 2026-09-30
- Project duration
- 72 months (the same as in the proposal)
- Project status
- Pending project
Project description
Download the project description in a pdf file
Note — project descriptions were prepared by the authors of the applications themselves and placed in the system in an unchanged form.
Information in the final report
Publication in academic press/journals (2)
-
Achieving Service Level and Sustainability Goals Through Targeted Inventory Forecasting in Re-Order Point Systems with Fill Rate Commitments
- Authors:
- Wojtasik J., Bruzda J.
- Academic press:
- Sustainability (year: 2025, volume: 17, pages: 10192), Publisher: MDPI
- Status:
- Published
- DOI:
- 10.3390/su172210192 – link to the publication
-
Risk Analysis in Basestock Inventory Systems Under Short-term Fill Rate Audits
- Authors:
- Wojtasik J., Bruzda J., Abbasi B.
- Academic press:
- IISE Transactions (year: 2026, volume: 58, pages: 586–604), Publisher: Taylor and Francis
- Status:
- Published
- DOI:
- 10.1080/24725854.2025.2519789 – link to the publication