On Characterizing weak defining hyperplanes (weak Facets) in DEA with Constant Returns to Scale Technology

Characterizing and finding full dimensional efficient facets of PPS with constant returns to scale technology

characterizing and finding full dimensional efficient facets of pps with constant returns to scale technology

Characterizing and finding full dimensional efficient facets of PPS with constant returns to scale technology

In DEA (Data Envelopment Analysis), the Full Dimensional Efficient Facets (FDEFs) of PPS (Production Possibility Set) play a significant role and have many useful applications. In this research, we, first, provide a detailed characterization of the structure of FDEFs of the PPS with constant returns to scale technology, using basic concepts of the polyhedral sets theory. Then, using the mention...

‎f‎inding the defining hyperplanes of production possibility set with ‎variable‎ returns to scale using the linear independent ‎vectors‎‎

The Production Possibility Set (PPS) is defined as the set of all inputs and outputs of a system in which inputs can produce outputs‎. ‎In Data Envelopment Analysis (DEA)‎, ‎it is highly important to identify the defining hyperplanes and especially the strong defining hyperplanes of the empirical PPS‎. ‎Although DEA models can determine the efficiency of a Decision Making Unit (DMU)‎, ‎but they...

Two-stage Production Systems under Variable Returns to Scale Technology: A DEA Approach

Data envelopment analysis (DEA) is a non-parametric approach for performance analysis of decision making units (DMUs) which uses a set of inputs to produce a set of outputs without the need to consider internal operations of each unit. In recent years, there have been various studies dealt with two-stage production systems, i.e. systems which consume some inputs in their first stage to produce ...