Combined Data Envelopment Analysis and Analytical Hierarchy Process Methods to obtain the Favorable Weights from Pairwise Comparison Matrix

Finding the favorable weights from pairwise comparison matrices is very important to rank the alternatives in Multi Attribute Decision Making (MADM) concept. Using Linear Programming has considered to develop this field during recent researches. Combined Analytic Hierarchy Process and Data Envelopment Analysis considered by some researches to find the weights. Decreasing the numerical procedures is vital because of using linear programming in proposed models. In this paper we are going to present some models to generate the favorable weights from a pairwise comparison matrix combing Analytic Hierarchy Process (AHP) and Data Envelopment Analysis (DEA) models. First we address a history and applications of AHP and then some notes on DEA models. Finally three DEA models are proposed to find the weights. In this way we tried to decrease the computational process by decreasing the number of constraints and variables of proposed models. Some numerical examples are putted forward to illustrate our approaches.