Dynamic productivity improvement in a model with multiple processes

Michael Brock and Jørgen Tind

Mathematical Methods of Operations Research, 2001, vol. 54, issue 3, 387-393

Abstract: We study the situation where there are a number of on-going production processes each yielding a state-dependent standard reward in discrete time. At each time step one may select at most one of these processes for improvement; the selected process will yield a state-dependent non-standard reward (or cost) at that time step and change its state according to a Markov chain. We show that this model can be cast into a bandit formulation with constructed rewards and we characterize the optimal policy. Finally, we present a numerical example. Copyright Springer-Verlag Berlin Heidelberg 2001

Keywords: Key words: Dynamic programming; production; bandit models (search for similar items in EconPapers)
Date: 2001
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DOI: 10.1007/s001860100166

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