APPROXIMATIONS AND SENSITIVITY IN MULTIOBJECTIVE RESOURCE-ALLOCATION

This study addresses the modeling of resource allocation planning problems having uncertainties, multiple competing objectives, organizational constraints, and continuous decision variables. The application of multiobjective decision analysis leads to a nonlinear programming formulation in which the objective function is the expectation of a multiattribute utility function. If a set of independence conditions holds, this function can be decomposed into appropriately scaled sums and products of one-dimensional expected utility functions. Approximations that greatly simplify the data acquisition for, and the construction of, the one-dimensional expected utility functions are discussed.