Time-dependent queueing models are important since most of real-life problems are time-dependent. We develop a numerical approximation algorithm for the mean, variance and higher-order moments of the number of entities in the system at time t for the Ph(t)/Ph(t)/s/c queueing model. This model can be thought as a reparameterization to the G(t)/GI(t)/s. Our approach is to partition the state space into known and identifiable structures, such as the M(t)/M(t)/s/c or M(t)/M(t)/1 queueing models. We then use the Polya-Eggenberger distribution to approximate certain unknown probabilities via a two-moment matching algorithm. We describe the necessary steps to validate the approximation and measure the accuracy of the model. / Master of Science

A deterministic change to a time-varying queueing model is described as either changing the number of entities, the queue capacity, or the number of servers in the system at selected times. We use a surrogate distribution for N(t), the number of entities in the system at time t, to approximate deterministic changes to the Ph(t)/Ph(t)/1/c and the Ph(t)/M(t)/s/c queueing models. We develop a solution technique to minimize the number of state probabilities to be approximated. / Master of Science

<p> An investigation into the impact of the Reynolds Bauxite Company, a decentralized industry in north-central Jamaica, on the spatial pattern of employment in the surrounding area. The spatial impact is simulated using the Polya-Eggenberger distribution. </p> / Thesis / Master of Arts (MA)