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This paper develops a model for allocating cross-trained workers at the beginning of a shift in a multidepartment service environment. It assumes departments are trying to maximize objective functions that are concave with respect to the number of workers assigned. Worker capabilities are described by parameters that range from zero to one, with fractional values representing workers who are less than fully qualified. The nonlinear programming model presented is a variant of the generalized assignment problem. The model is used in a series of experiments to investigate the value of cross-utilization as a function of factors such as demand variability and levels of cross-training. Results show that the benefits of cross-utilization can be substantial, and in many cases a small degree of cross-training can capture most of the benefits. Beyond a certain amount additional cross-training adds little additional value, and the preferred amount depends heavily on the level of demand variability.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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