A Goal Programming Approach for Development of Common Weights in Network DEA

Abstract

Data Envelopment Analysis (DEA) is a powerful analytical technique for measuring the relative efficiency for a set of Decision Making Units (DMUs) based on their inputs and outputs. There are weaknesses in conventional models DEA. Most important of which is the weight shift input and output which makes the efficiency of Decision Making Units with different weights measured. A characteristic of Traditional DEA models is that it allows DMUs to measure their maximum efficiency score with the most favorable weights. As well as the conventional DEA models are not focused network of evaluation units. In this paper we propose to correct the weaknesses the common set of weights (CSW) in network DEA model based on the Goal programming approach. To test the effectiveness of the proposed model and solve real data is used by insurance companies active in Qazvin province. The model presented in this paper units decide on a similar scale with a set of weights for neutral evaluation is common. Proposed approach helps policy makers to better understand the strengths and weaknesses of DMUs and try to promote the strengths and remove weaknesses to improve the efficiency and ranking of given DMUs.

Keywords

• data envelopment analysis
• common weights
• network dea
• goal programming