This paper uses advance order data and historical demand data from a manufacturing shop and from a service operation to develop and test a forecasting methodology for predicting customer demand over a forecast horizon. The proposed methodology uses simple linear regression to model the relationship between a total demand ratio and a partial demand ratio. Comparison of the proposed model to a standard regression approach and a commonly used multiplicative model showed that the proposed model exhibited the greatest forecast accuracy.

Interruptions to the server in an outpatient clinic environment have received limited attention in the appointment scheduling literature. However, explicitly modeling interruptions on the part of the doctor may have an impact on the optimal appointment schedule and consequently, on patient waiting times. This is explored with a simulation optimization model that is based on data from time studies and interviews with medical professionals from multiple outpatient clinics. The results show a plateau-dome scheduling rule for practical implementation to be robust for low interruption rates and a traditional dome pattern for higher levels of interruptions. In addition, if clinic operations are such that doctors are able to adjust their behavior to complete all work during the session, then the schedule is invariant to changes in the interruption rate.

ANALYZE AND EXPLAIN IN YOUR OWN WORDS. NO PLAGIARISM (I WILL CHECK). I WILL DOWNVOTE