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Steady State Distributions for Manpower Models under Conditions of Growth

机译：增长条件下人力模型的稳态分布

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Markov Chain models have been used to forecast stocks in a wide range of manpower systems. Studies have been done in many areas such as education planning, hospital planning, manufacturing, private research and development, a women's military unit, the civilian work force supporting the U,S. Navy and state police organization. This thesis looks at such systems under conditions of change and develops the equations that describe the steady state distribution of personnel. The conditions of change include systems where recruitment is constant, increasing (decreasing) additively, or increasing (decreasing) multiplicatively and systems where the changes in total system size are additively or multiplicatively increasing (decreasing). Numerical examples utilizing these models are provided, along with a computer program of the formulas written in the language APL.

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