DEA Model with Hesitant Fuzzy Polyhedral Set in Benchmarking
Abstract
Data Envelopment Analysis (DEA) method is a linear programming approach that has been widely used as a framework for evaluating efficiency and measurement. DEA decision making is often faced with situations where the existing DMU has input and output that contains fuzzy and hesitant elements so that it is difficult to make efficiency measurements. This study will design a DEA model in the state of inputs and outputs that contain hesitant elements by using polyhedral uncertainty sets. The results of this study are expected to produce a benchmarking model with DEA that can overcome the hesitant element and have the advantage of using a polyhedral uncertainty set that can measure the linearity of the nominal problem.
- Publication:
-
Journal of Physics Conference Series
- Pub Date:
- November 2019
- DOI:
- 10.1088/1742-6596/1361/1/012033
- Bibcode:
- 2019JPhCS1361a2033A