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UID:70@lincs.fr
DTSTART;TZID=Europe/Paris:20151216T140000
DTEND;TZID=Europe/Paris:20151216T150000
DTSTAMP:20170313T170938Z
URL:https://www.lincs.fr/events/dynamic-control-of-stochastic-and-fluid-re
 source-sharing-systems/
SUMMARY:Dynamic control of stochastic and fluid resource-sharing systems
DESCRIPTION:We study the dynamic control of resource-sharing systems that
 arise in various domains: e.g. inventory management\, healthcare and
 communication networks. We aim at efficiently allocating the available
 resources among competing projects according to a certain performance
 criteria. These type of problems have a stochastic nature and may be very
 complex to solve. We therefore focus on developing well-performing
 heuristics. Firstly\, we consider the framework of Restless Bandit
 Problems\, which is a general class of dynamic stochastic optimization
 problems. Relaxing the sample-path constraint in the optimization problem
 enables to define an index-based heuristic for the original constrained
 model\, the so-called Whittle index policy. We derive a closed-form
 expression for the Whittle index as a function of the steady-state
 probabilities for the case in which bandits (projects) evolve in a
 birth-and-death fashion. This expression requires several technical
 conditions to be verified\, and in addition\, it can only be computed
 explicitly in specific cases. In the particular case of a multi-class
 abandonment queue\, we further prove that the Whittle index policy is
 asymptotically optimal in the light-traffic and heavy-traffic regimes.
 Secondly\, we derive heuristics by approximating the stochastic
 resource-sharing systems with deterministic fluid models. We first
 formulate a fluid version of the relaxed optimization problem\, and we
 develop a fluid index policy. The fluid index can always be computed
 explicitly and hence overcomes the technical issues that arise when
 calculating the Whittle index. We apply the Whittle index and the fluid
 index policies to several systems: e.g. power-aware server-farms\,
 opportunistic scheduling in wireless systems\, and make-to-stock problems
 with perishable items. We show numerically that both index policies are
 nearly optimal.
CATEGORIES:Seminars
LOCATION:LINCS Meeting Room 40\, 23\, avenue d'Italie\, Paris\, 75013\,
 France
GEO:48.8283983;2.3568972000000485
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TZID:Europe/Paris
X-LIC-LOCATION:Europe/Paris
BEGIN:STANDARD
DTSTART:20151025T020000
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
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