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| Abstract | ||||
| I will consider a call center
model with m input flows and r pools of agents, allowing the m-vector ? of
instantaneous arrival rates to be time-dependent and to vary stochastically.
Two levels of call center management are of interest: staffing the r pools
of agents, and dynamically routing calls to agents. In the research that I
will describe, the system manager¨s objective is to minimize the sum of
personnel costs and congestion costs, where the latter term includes both
holding costs abandonment penalties. The two-level problem identified above is generally intractable in its "exact" form, but progress can be made by seeking policies that are asymptotically optimal in some limiting parameter regime. This mode of analysis might be characterized as a mathematically respectable form of reduced expectations. I will describe a limiting parameter regime that is natural for call centers and relatively easy to analyze, but apparently novel in the literature of applied probability. In that asymptotic regime, optimal staffing reduces to a stochastic programming problem that (i) uses a strikingly simple distillation of the original system data, and (ii) can readily be solved for problems of realistic scale, using a combination of linear programming and Monte Carlo simulation. The corresponding method for dynamic call routing is one that makes quasi-static server allocations over relatively short time intervals, based on the solution of a certain linear program that is frequently resolved using real-time data. * Joint work with Assaf Zeevi and Achal Bassamboo. |
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| Brief Biography | ||||
| J. MICHAEL HARRlSON is the Adams Distinguished Professor of Management in the Graduate School of Business, Stanford University. He earned a B.S. degree in industrial engineering from Lehigh University, an M.S. in industrial engineering from Stanford, and a Ph.D. in operations research from Stanford before joining the faculty of the Graduate School of Business in 1970. He has developed and analyzed stochastic models in several different domains related to business, including mathematical finance and processing network theory. His current research is focused on call center management, dynamic pricing, and revenue management. Professor Harrison was honored by INFORMS with its Expository Writing Award in 1998, and with the Lanchester Prize for best research publication in 2001. He is a member of INFORMS, a fellow of the Institute for Mathematical Statistics, and associate editor of the Annals of Applied Probability. |