Using client-variance information to improve dynamic appointment scheduling performance

Clients of services expect short waiting times and servers desire short per iods of non-productive time. One of the areas where this is most important is appointment scheduling systems. Recent research has indicated that using information about clients' service time variability can simultaneously red uce waiting times and server idle time. In this study, a more realistic, dy namic appointment-scheduling environment is developed and used to analyze s everal scheduling rules. Additional complexities considered in this study i nclude: continuously distributed service-time variances, special client app ointment requests, and appointment-scheduler uncertainty. Results show that rules using client-variance information are still best at minimizing waiti ng time and idle time with the additional complexities. In fact, these rule s perform best when client variance is large. However, on measures related to clients requesting specific appointment slots the results are not as cle ar cut. A key factor for these measures is the distribution of the desired slots. When the desired slots are near the end of the appointment schedulin g period, traditional rules like first-call-first-appointment perform bette r on client appointment request measures. (C) 2000 Elsevier Science Ltd. Al l rights reserved.