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Staffing call centers under arrival-rate uncertainty with Bayesian updates |
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| Authors: | Jing Zan John J. Hasenbein David P. Morton Vijay Mehrotra |
| Affiliation: | 1. Uber Technologies Inc., 555 Market Street, San Francisco, CA 94105, United States;2. Graduate Program in Operations Research and Industrial Engineering, Department of Mechanical Engineering, University of Texas at Austin, Austin, TX 78712, United States;3. Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL 60208, United States;4. University of San Francisco, Department of Business Analytics and Information Systems, School of Management, 2130 Fulton Street, San Francisco CA 94117, United States |
| Abstract: | We consider the problem of staffing service centers with quality-of-service constraints. We focus on the case where the arrival rates are uncertain. We introduce formulations that handle staffing decisions made over two decision periods, minimizing the staffing costs over the stages while satisfying a service quality constraint on the second stage operation. A Bayesian update is used to obtain the second-stage arrival-rate distribution based on the first stage prior arrival-rate distribution and the observations in the first stage. |
| Keywords: | Call center staffing Quality-of-service Erlang-C Stochastic programming Bayesian update |
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