چکیده:
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
خلاصه ماشینی:
"Relation between Imprecise DESA and MOLP Methods Marzieh Moradi Dalini, Abbas Ali Noura* Department of Mathematics, Kerman Branch, Islamic Aazd University, Kerman, Iran (Received: May 13, 2017; Revised: December 11, 2017; Accepted: December 26, 2017) Abstract It is generally accepted that Data Envelopment Analysis (DEA) is a method for indicating efficiency.
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.
It would be worth mentioning that the important result obtained by this equivalence relation is using interactive MOLP to solve DEA model and obtain Most Preferred Solution (MPS).
Project algorithm is defined as follows: Step 1: In the initial stage of the process, we can obtain the best value for both inputs and outputs,And denoted by f ¢ = f (l* ) , f ¢ = ~ (l* )(View the image of this page) Step 2: During the second phase, we find the set of initial weighting parameters for all DMUs, and reach the first answer of the decision variables(View the image of this page)After generating reference total output and input, we can then select the most preferred solution and the interactive process will be finished.
The results of this study suggest that interactive Project algorithm is suitable for solving the imprecise DESA problem and our method could achieve the MPS."