Summary
The separation of manpower forecasting into a demand forecast and a supply forecast emphasizes that each depends on quite different sources of information. The demand forecast is based primarily on an estimate of sales, which is then transformed into the number and type of personnel needed to produce and sell the company's products. The information for forecasting internal supply can often be treated as if it were independent of the external environment and is often available within the firm. If a matrix representing the probability of transition from one job classification to another can be prepared for the relevant classifications, Markov‐chain theory can be used to generate a forecast of internal manpower supply.
Modeling large systems with either an optimization or a simulation method has several disadvantages. Simulation is usually expensive if adequate detail and experimental designs are employed. Complete detail in optimization models may press the bounds of computability. A recursive approach integrating both types of models is presented. The recursive approach involves, an allocation of resources by optimization models at an aggregate level. At this level computation is not difficult and broad alternatives can be easily explored. Simulation models can then be designed to address detailed questions of productivity of resources, discreteness, and complex relationships. The simulation can use the particular schedules generated by the optimization so that experimental designs can be limited in size. The revised productivities can then be input to the optimization model for a more refined optimal solution. The recursive approach has been applied to the strategic mobility system problem in reaching decisions for the size of transportation forces for the DOD. A linear programming model provides optimal allocation of overall mobility system vehicles and schedules. Two simulation models, an airlift model and a sealift model, provide productivity estimates and tests of capability.
The basic concepts and application of spectral analysis are explained. Stationary time series and autocorrelation are first defined. Autocorrelation is related to the familiar concepts of variance and covariance. The
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Large scale Humanitarian Assistance/Disaster Relief (HA/DR) operations often require the intervention and aid of various agencies from all over the world. As a result, HA/DR operations involve many negotiation and coordination issues. Although a number of studies have emphasized computer assistance for negotiations, it remains unclear how such information and communication technology could be employed in HA/DR operations. This paper presents a framework for developing a Global Information Network (GIN) for HA/DR operation. It derives a set of functional requirements and proposes system components for GIN that would facilitate HA/DR operations.
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