Abstract
An asymptotic analysis for a large class of stochastic optimization problems arising in manufacturing is presented. A typical example of the problems considered in this paper is a production planning problem with random capacity and demand. In this example, it is assumed that the capacity of the system fluctuates faster than the other quantities. The general model considered here also has a fast controlled Markov process in its state description. By using the difference in the time scales of different quantities, the problem is simplified by “averaging” out the fast process. Then asymptotically optimal strategies are constructed from the optimal solutions of the limiting problems. The proofs of these results use the theory of viscosity solutions to dynamic programming equations. However, the formal construction of the asymptotically optimal strategies does not require knowledge of this theory.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
