Real-Time Delay Prediction in Customer Service Systems



Motivated by the desire to make delay announcements to arriving customers, we study alternative ways of predicting customer delay in many-server service systems. Our delay predictors differ in the type and amount of information that they use about the system. We introduce predictors that effectively cope with real-life phenomena, such as customer abandonment (impatience), time-varying arrival rates, and general service-time distributions. We use computer simulation and heavy-traffic analysis to verify that our proposed predictors outperform several natural alternatives.
Contact information:
Dr. F. Sting