Relation Between Imprecise DESA and MOLP Methods

It is generally accepted that Data Envelopment Analysis (DEA) is a method for indicating efficiency. The DEA method has many applications in the field of calculating the relative efficiency of Decision Making Units (DMU) in explicit input-output environments. Regarding imprecise data, several definitions of efficiency can be found. The aim of our work is showing an equivalence relation between one of the models of DEA with imprecise data and Multiple Objective Linear Programming (MOLP). The relation between DEA and MOLP was studied to use interactive multiple objective models for solving the DEA problem in exact situation and find the most preferred solution. The aim of this study is to analyze an equivalent relation between imprecise DEA (IDEA) and MOLP models. In this context, we tried to solve IDEA models with interactive project procedure. The Project method is the responsible method, because it can estimate any efficient solution, and it indicates Most Preferred Solution (MPS). In addition, we will use the Data Envelopment Scenario Analysis (DESA) model. The main characteristic of DESA model is to decrease all inputs and increase all outputs and estimate one problem instead of n problems.