Allocating limited resources among competing candidates is an important problem in management. In this paper, we describe a structured and flexible approach to resource allocation using logic-evolved decision (LED) analysis. LED analysis uses logic models to generate an exhaustive set of competing alternatives and the inferential model that is used for preference ordering of these alternatives. The inferential models can use data in numerical, linguistic, or mixed forms; uncertainty in the evaluation results can be expressed using probabilistic- or linguistic-based methods. We illustrate the use of LED analysis for an allocation problem with numerical input data and for an allocation problem with only linguistic input data.

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