Evaluation of Benchmark Information with Least-distance Measurement Model for Non-convex Frontiers and Petri Net
Behnam Barzegar, Reza Shahverdi · Indian Journal of Science and Technology · 2011
Data Envelopment Analysis (DEA) is efficient analysis for similar decision making units (DMUs). It provides a ranking of DMUs relative to each other. DAE in addition to determining efficiency level, provides situations for removing inefficiency by using evaluated benchmark information. The Least-Distance Measurement model is proposed in order to shifting inefficiency to the nearest efficient unit which may not applied in real-world problems about convex technology (i.e., the convexity of the production probability function); thus, expanding DEA to non-convexity technology would be improved the potential of applying the Least-Distance Measurement model. This paper proposes extension of Least-Distance Measurement model in non-convexity technology and we will explore Petri Nets for modeling a leastdistance measurement in non-convex space.