Efficient Computation and Long Range Optimization Applications Using a Two-Characteristic Markov-Type Manpower Flow Model.

摘要

In the past the author has compared and contrasted Markov and longitudinal manpower flow models. The Markov model requires relatively little data and has been widely analyzed. The longitudinal model incorporates more realistic personnel flows, but requires extensive data which is not always available. Hayne and Marshall have analyzed a two-characteristic Markov model which can be viewed as a hybrid of the Markov and longitudinal models. The purpose of this paper is to show how efficient computational methods can be used with the two-characteritsic model by exploiting the special structure of its underlying matrix. These methods make possible the efficient use of this basic flow model in optimization models.