Using linear programming to analyze and optimize stochastic flow lines

Stefan Helber (), Katja Schimmelpfeng, Raik Stolletz and Svenja Lagershausen

Hannover Economic Papers (HEP) from Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät

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 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.

Keywords: Flow lines; random processing times; performance evaluation; buffer allocation; linear programming; simulation. (search for similar items in EconPapers)
JEL-codes: C61 (search for similar items in EconPapers)
Pages: 20 pages
Date: 2008-02
New Economics Papers: this item is included in nep-cmp and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Related works:
Journal Article: Using linear programming to analyze and optimize stochastic flow lines (2011)
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