methods of optimization in imprecise data envelopment analysis

in this paper imprecise target models has been proposed to investigate the relation between imprecise data envelopment analysis (idea) and mini-max reference point formulations. through these models, the decision makers' preferences are involved in interactive trade-off analysis procedures in multiple objective linear programming with imprecise data. in addition, the gradient projection type method can be suggested to determine a normal vector at a given efficient solution on the efficient frontier and to establish an interactive procedure for searching for the most preferred solution (mps) that maximizes the decision maker implicit utility function