Manuel Schlenkrich, Wolfgang Seiringer, Klaus Altendorfer, Sophie N. Parragh
arXiv 22 Feb 2024 · Econometrics · 2 citations (OpenAlex)
arXiv:2402.14506 · PDF · DOI · OpenAlex · Extracted main text
Production planning must account for uncertainty in a production system, arising from fluctuating demand forecasts. Therefore, this article focuses on the integration of updated customer demand into the rolling horizon planning cycle. We use scenario-based stochastic programming to solve capacitated lot sizing problems under stochastic demand in a rolling horizon environment. This environment is replicated using a discrete event simulation-optimization framework, where the optimization problem is periodically solved, leveraging the latest demand information to continually adjust the production plan. We evaluate the stochastic optimization approach and compare its performance to solving a deterministic lot sizing model, using expected demand figures as input, as well as to standard Material Requirements Planning (MRP). In the simulation study, we analyze three different customer behaviors related to forecasting, along with four levels of shop load, within a multi-item and multi-stage production system. We test a range of significant parameter values for the three planning methods and compute the overall costs to benchmark them. The results show that the production plans obtained by MRP are outperformed by deterministic and stochastic optimization. Particularly, when facing tight resource restrictions and rising uncertainty in customer demand, the use of stochastic optimization becomes preferable compared to deterministic optimization.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | barticle Gansterer, M., Almeder, C., Hartl, R.F.: Simulation-based o… (2014) ) 10.1016/j.ijpe.2013.10.016 barticle | 0.843 | 3 | 3 | 100% |
| 2 | bbook Hopp, W.J., Spearman, M.L.: Factory Physics, third edition edn… (2011) ) bbook | 0.737 | 3 | 2 | 100% |
| 3 | barticle Heath, D.C., Jackson, P.L.: Modeling the evolution of deman… (1994) ) 10.1080/07408179408966604 barticle | 0.644 | 2 | 2 | 100% |
| 4 | barticle Juan, A.A., Faulin, J., Grasman, S.E., Rabe, M., Figueira,… (2015) ) 10.1016/j.orp.2015.03.001 barticle | 0.644 | 2 | 2 | 100% |
| 5 | barticle Norouzi, A., Uzsoy, R.: Modeling the evolution of dependenc… (2014) ) 10.1080/0740817X.2013.803637 barticle | 0.644 | 2 | 2 | 100% |
| 6 | bbook Orlicky, J.: Materials Requeriments Planning ; the New Way of… (1975) ) bbook | 0.644 | 2 | 2 | 100% |
| 7 | barticle Almeder, C., Gansterer, M., Hartl, R.F.: Simulation and opt… (2009) ) 10.1007/s00291-007-0118-z barticle | 0.644 | 2 | 2 | 100% |
| 8 | barticle Forel, A., Grunow, M.: Dynamic stochastic lot sizing with f… (2023) ) 10.1111/poms.13881 barticle | 0.644 | 2 | 2 | 100% |
| 9 | barticle Altendorfer, K., Felberbauer, T.: Forecast and production o… (2023) ) 10.1016/j.simpat.2023.102740 barticle | 0.585 | 3 | 1 | 100% |
| 10 | barticle Thevenin, S., Adulyasak, Y., Cordeau, J.: Material Requirem… (2021) ) 10.1111/poms.13277 barticle | 0.585 | 3 | 1 | 100% |
Showing the top 10 of 43 scored citations.