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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2451/14638
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| Title: | Staffing and Control of Large-Scale Service Systems with Multiple
Customer Classes and Fully Flexible Servers |
| Authors: | Gurvich, Itay
Armony, Mor
Mandelbaum, Avishai |
| Issue Date: | 2005 |
| Publisher: | Stern School of Business, New York University |
| Series/Report no.: | OM-2005-10 |
| Abstract: | We study large-scale service systems with multiple customer classes and
many statistically identical servers. The following question is
addressed: How many servers are required (staffing) and how does one
match them with customers (control) in order to minimize cost or
maximize profit, subject to quality of service (QoS) constraints? We
tackle this question by characterizing scheduling and staffing schemes
that are asymptotically optimal in the limit, as system load grows to
infinity. The main asymptotic regime considered is the many-server
heavy-traffic Quality and Efficiency Driven (QED) regime. The
Efficiency Driven (ED) regime is also studied. In the QED regime, which
was formally introduced by Halfin and Whitt, a delicate balance is
obtained between server efficiencies and quality of service. This
balance is enabled by the economies of scale associated with the system
size. Our main findings are: a) Decoupling of staffing and control,
namely (i) Staffing disregards the multi-class nature of the system and
is analogous to the staffing of a single class system with the same
aggregate demand and the lowest priority class cost and QoS parameters,
and (ii) Class level service differentiation is obtained by using a
simple threshold-priority (TP) control (with state-independent
thresholds), b) Robustness of the staffing and control rules: In the
QED regime, our proposed Square-Root Safety (SRS) staffing rule and TP
control are asymptotically optimal with respect to various problem
formulations and model assumptions. c) The QED and ED regimes are
obtained as solutions of the joint staffing and control problem rather
than as assumptions. |
| URI: | http://hdl.handle.net/2451/14638 |
| Appears in Collections: | IOMS: Operations Management Working Papers
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