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Hybrid Algorithms for Redesigning MRP
3-year research project in cooperation with the University of Applied Sciences Upper Austria, funded by the Austrian Science Fund (FWF).
Material Requirements Planning (or MRP for short) concerns medium-term production planning within the widely applied hierarchical production planning framework. It used to determine which items are needed at what due date, when to start their production, and what amount to produce. In spite of its popularity in practice, traditional MRP suffers from a number of problems: machine capacity is assumed to be infinite, demand is assumed to be deterministic, production and replenishment lead times are assumed to be constant (and independent of current system load), and rolling horizon planning aspects are ignored.
The overall aim of this project is to develop efficient modeling and solution approaches to overcome all of these drawbacks and to provide (close to) optimal mid-term production plans. A main focus is the rolling horizon planning aspect in combination with stochastic demand and capacitated production system behavior and the integration of simulation based and optimization based approaches.
More information can be found here Project Webpage at FH OÖ, opens an external URL in a new window
Research Project
Hybrid Algorithms for Redesigning MRP
Funding Agency
Austrian Science Fund (FWF)
Duration
October 1, 2020 - September 30, 2023
Project lead
Klaus Altendorfer
(FH OÖ)
Sophie Parragh
(JKU)
Contact
sophie.parragh@jku.at
People
Name | |
---|---|
Univ.-Prof.in Sophie Parragh, PhD | |
Role | Lead |
Contact | sophie.parragh(at)jku.at |
DI Manuel Schlenkrich, BSc BSc | |
Role | Researcher |
Contact | manuel.schlenkrich(at)jku.at |
Name | Role | Contact | |
---|---|---|---|
Univ.-Prof.in Sophie Parragh, PhD | Lead | sophie.parragh(at)jku.at | |
DI Manuel Schlenkrich, BSc BSc | Researcher | manuel.schlenkrich(at)jku.at |
Presentations
- Schlenkrich M., Seiringer W., Altendorfer K., Parragh S. N. (2023) Rolling horizon production planning with forecast evolution based stochastic optimization, OR 2023, Hamburg, Germany, 30.08.2023
- Schlenkrich M., Parragh S.N. (2022) Separating setup and quantity decisions in stochastic lot sizing models, OR 2022, Karlsruhe, Germany. 07.09.2022.
- Schlenkrich M., Parragh S.N. (2022) The impact of risk aversion and flexibility on stochastic and robust lot sizing decisions, EURO 2022, Espoo, Finnland, 04.07.2022.
- Schlenkrich M., Parragh S.N. (2022) Computational analysis of stochastic and robust optimization models for capacitated lot sizing under uncertain customer demand, Manufacturing and Service Operations Management Conference 2022, Munich, Germany, 27.06.2022
- Schlenkrich M., Parragh S.N. (2021) Robust optimization models for MRP – a comparison to stochastic programming approaches and a decomposition based solution method, OR 2021, Bern/online, 02.09.2021
Publications
- Schlenkrich, M., Seiringer, W., Altendorfer, K., Parragh, S.N. (2024). Enhancing Rolling Horizon Production Planning Through Stochastic Optimization Evaluated by Means of Simulation. https://arxiv.org/abs/2402.14506v1, opens an external URL in a new window (submitted)
- Schlenkrich, M., Parragh, S.N. (2024). Capacitated multi-Item multi-echelon lot sizing with setup carry-over under uncertain demand. International Journal of Production Economics, 277, 109379. https://doi.org/10.1016/j.ijpe.2024.109379, opens an external URL in a new window. Available at SSRN: https://ssrn.com/abstract=4530599, opens an external URL in a new window or http://dx.doi.org/10.2139/ssrn.4530599, opens an external URL in a new window
Media
- Unsicherheit mit Sicherheit, Logistik Appetizer, Oktober 2021, https://www.bvl.at/2021/12/16/unsicherheit-mit-sicherheit-2/, opens an external URL in a new window
