Computational Performance Bounds for Markov Chains With Applications

Computational Performance Bounds for Markov Chains With Applications

For Markov chains exhibiting translation invariance of their transition probabilities on polyhedra covering the state space, we develop computational performance bounds for key measures of system performance. Duality allows us to obtain linear programming performance bounds. The Markov chains consid...

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Veröffentlicht in:IEEE transactions on automatic control 2008-06, Vol.53 (5), p.1306-1311
Hauptverfasser: Morrison, J.R., Kumar, P.R.
Format: Artikel
Sprache:eng
Schlagworte:
Applied sciences
Automatic control
Computation
Cost function
Dynamic programming
Exact sciences and technology
Linear programming
Manufacturing automation
Markov chains
Markov processes
Networks
Operational research and scientific management
Operational research. Management science
Policies
Polyhedrons
Queueing analysis
Queuing theory. Traffic theory
Semiconductor device manufacture
State-space methods
Supply chains
System performance
Transition probabilities
Translations
Transportation
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Zusammenfassung:For Markov chains exhibiting translation invariance of their transition probabilities on polyhedra covering the state space, we develop computational performance bounds for key measures of system performance. Duality allows us to obtain linear programming performance bounds. The Markov chains considered can be used to model multiclass queueing networks operating under affine index policies, a class of policies which subsume many that have been proposed.
ISSN:0018-9286
1558-2523
DOI:10.1109/TAC.2008.921013