An Efficiency Improvement Approach in Data Envelopment Analysis (DEA

There are some ways to achieve the targets for inefficient decision making units (DMUs) in basic Data Envelopment Analysis (DEA) models which are used in efficiency improvement approaches. But, there are some difficulties for using efficiency improvement approaches which obtain by DEA models. In other word, there isn't any choice for efficiency improvement level; hence, these efficiency improvement approaches aren't selective and gradual. Different methods have been introduced under this circumstance (see 2, 3), which Inverse DEA models are the important group of them [3], but, these methods make some assumptions which, are sorely restrictive in real cases. Hence, a general and efficient method under this circumstance is necessary. In this paper, we propose an efficiency improvement approach which decision make can choose growth in targets for next period and it doesn't have any forces for becoming efficient.