Abstract.
An optimal production planning for a stochastic manufacturing system is considered. The system consists of a single, failure-prone machine that produces a finite number of different products. The objective is to determine a rate of production that minimizes an average cost per unit time criterion where the demand is random. The results given in this paper are based on some large deviation estimates and the Hamilton-Jacobi-Bellman equations for convex functions.
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Manuscript received: October 2000/Final version received: May 2001
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Duncan, T., Pasik-Duncan, B. & Stettner, Ł. Average cost per unit time control of stochastic manufacturing systems: Revisited. Mathematical Methods of OR 54, 259–278 (2001). https://doi.org/10.1007/s001860100146
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DOI: https://doi.org/10.1007/s001860100146