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Using linear programming to analyze and optimize stochastic flow lines


Helber, Stefan ; Schimmelpfeng, Katja ; Stolletz, Raik ; Lagershausen, Svenja



DOI: https://doi.org/10.1007/s10479-010-0692-3
URL: https://link.springer.com/article/10.1007%2Fs10479...
Additional URL: https://www.researchgate.net/publication/5091164_U...
Document Type: Article
Year of publication: 2011
The title of a journal, publication series: Annals of Operations Research
Volume: 182
Issue number: 1
Page range: 193-211
Place of publication: New York, NY [u.a.]
Publishing house: Springer Science + Business Media B.V.
ISSN: 0254-5330 , 1572-9338
Publication language: English
Institution: Business School > ABWL u. Produktion (Stolletz)
Subject: 650 Management
Abstract: This paper presents a linear programming approach to analyze and optimize flow lines with limited buffer capacities and stochastic processing times. The basic idea is to solve a huge but simple linear program that models an entire simulation run of a multi-stage production process in discrete time, to determine a production rate estimate. As our methodology is purely numerical, it offers the full modeling flexibility of stochastic simulation with respect to the probability distribution of processing times. However, unlike discrete-event simulation models, it also offers the optimization power of linear programming and hence allows us to solve buffer allocation problems. We show under which conditions our method works well by comparing its results to exact values for two-machine models and approximate simulation results for longer lines.

Dieser Datensatz wurde nicht während einer Tätigkeit an der Universität Mannheim veröffentlicht, dies ist eine Externe Publikation.




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Helber, Stefan ; Schimmelpfeng, Katja ; Stolletz, Raik ; Lagershausen, Svenja (2011) Using linear programming to analyze and optimize stochastic flow lines. Annals of Operations Research New York, NY [u.a.] 182 1 193-211 [Article]


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