Methods of Optimization in Imprecise Data Envelopment Analysis

Abstract

<span style="font-size: medium;">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 </span>