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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