Approximate dynamic programming for stochastic linear control problems on compact state spaces |
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Authors: | Stefan Woerner Marco Laumanns Rico Zenklusen Apostolos Fertis |
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Affiliation: | 1. IBM Research, Saeumerstrasse 4, 8803 Rueschlikon, Switzerland;2. ETH Zurich, Raemistrasse 101, 8092 Zurich, Switzerland;3. SMA und Partner AG, Gubelstrasse 28, 8050 Zurich, Switzerland |
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Abstract: | This paper addresses Markov Decision Processes over compact state and action spaces. We investigate the special case of linear dynamics and piecewise-linear and convex immediate costs for the average cost criterion. This model is very general and covers many interesting examples, for instance in inventory management. Due to the curse of dimensionality, the problem is intractable and optimal policies usually cannot be computed, not even for instances of moderate size. |
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Keywords: | Dynamic programming Markov processes Inventory Dual sourcing Multiple sourcing |
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