The Law of Total Variance, new insights into queueing system behaviour, and new analytical models for time-dependent behaviour of M(t)/G/S(t) queues

Wednesday 6 December 2023, 1:00pm to 2:00pm


MAN - Mngt School Dormer LT14 WPA002 - View Map

Open to

Postgraduates, Public, Staff


Registration not required - just turn up

Event Details

Dave Worthington will present a seminar to the Management Science Department

Abstract: A recent Masters project investigated the extent to which established queueing theory models could be used to approximate the behaviour of a queueing system in which the service received by patients discharged from hospital consisted of decreasing numbers of home visits per day over the patient’s period of recovery.

We found that a discrete time Mbatch(t)/Geom1/S’(t) model provides good quality approximate results when compared to a more faithful simulation model of the real system if:

  • the mean service time and batch size distribution are chosen for the Mbatch(t)/Geom1/S’(t) model so that the mean and variance of the total amount of work associated with a patient matched (via the Law of Total Variance) that of the simulated model;
  • S’(t) is chosen to match the service capacity of the simulated model.

This finding has led to the idea of using discrete time Mbatch(t)/Geom1/S’(t) models to provide approximate analytical results for M(t)/G/S(t) queueing systems. Early empirical results are very promising; and the approach is computationally much cheaper than existing analytical approaches.

Contact Details

Name Gay Bentinck

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