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Title of Journal: Ann Oper Res

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Abbravation: Annals of Operations Research

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Springer US

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DOI

10.1007/978-94-015-8096-0_2

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1572-9338

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Using linear programming to analyze and optimize s

Authors: Stefan Helber Katja Schimmelpfeng Raik Stolletz Svenja Lagershausen
Publish Date: 2010/02/11
Volume: 182, Issue: 1, Pages: 193-211
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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 multistage 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 discreteevent 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 twomachine models and approximate simulation results for longer lines

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