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Hierarchical controls in stochastic manufacturing systems with convex costs
Authors:S. P. Sethi  Q. Zhang  X. Y. Zhou
Affiliation:(1) Faculty of Management, University of Toronto, Toronto, Ontario, Canada;(2) Department of Mathematics, University of Kentucky, Lexington, Kentucky
Abstract:This paper presents an extension of earlier research on heirarchical control of stochastic manufacturing systems with linear production costs. A new method is introduced to construct asymptotically optimal open-loop and feedback controls for manufacturing systems in which the rates of machine breakdown and repair are much larger than the rate of fluctuation in demand and rate of discounting of cost. This new approach allows us to carry out an asymptotic analysis on manufacturing systems with convex inventory/backlog and production costs as well as obtain error bound estimates for constructed open loop controls. Under appropriate conditions, an asymptotically optimal Lipschitz feedback control law is obtained.This work was partly supported by the NSERC Grant A4619, URIF, General Motors of Canada, and Manufacturing Research Corporation of Ontario.
Keywords:Stochastic manufacturing systems  convex production planning  hierarchical control  dynamic programming  viscosity solutions  convergence rates  error bounds
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