Thursday, 13:45 - 14:10 h, Room: MA 144

 

Jose Nino-Mora
Sufficient indexability conditions for real-state restless bandit projects via infinite-dimensional LP-based partial conservation laws

 

Abstract:
The multiarmed restless bandit (RB) problem concerns the optimal dynamic allocation of a shared resource to multiple stochastic projects, modeled as RBs, i.e., binary-action (active/passive) Markov decision processes. Although the problem is generally intractable, a unified approach to construct heuristic policies based on the Whittle priority index, or extensions thereof, has been shown to perform well in a variety of models. Deploying such an approach requires to establish the indexability (i.e., existence of the index) for the constituent RBs, and to evaluate the index numerically. This work presents the first general sufficient conditions for indexability of real-state RBs, motivated by applications that have drawn recent research attention. The conditions are based on an infinite-dimensional LP extension of partial conservation laws, an approach formerly introduced by the author to provide sufficient indexability conditions for discrete-state RBs. The approach further provides a practical means to evaluate the index. Applications will be discussed.

 

Talk 2 of the contributed session Thu.2.MA 144
"Large-scale and multi-stage stochastic optimization" [...]
Cluster 22
"Stochastic optimization" [...]

 

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