Random inputs and outputs in DEA models.

*(English)*Zbl 1179.90183
Boljunčić, Valter (ed.) et al., KOI 2006. 11th international conference on operational research, Pula, Croatia, September 27–29, 2006. Proceedings. Zagreb: Croatian Operational Research Society (ISBN 978-953-7498-11-5/pbk). 1-11 (2008).

Summary: Data Envelopment Analysis (DEA) is a method for evaluation of
relative efficiency of production units described by multiple inputs and outputs.
Standard DEA models are based on deterministic inputs and outputs. The paper
formulates basic DEA models supposing that inputs and outputs are continuous random
variables. Under this assumption the efficiency scores of production units are random
variables as well. Several approaches for description of random efficiency scores were
developed by various researches. They are mostly based on a formulation of LP
optimisation problems. The paper summarises some of these approaches and discusses
their advantages and disadvantages. Except this the aim of the paper is to describe the
properties of random efficiency scores by means of Monte Carlo experiments. The
experiments are realised within the MS Excel environment together with LINGO
optimisation solver and Crystal Ball add-in application for Monte Carlo analysis in
spreadsheets. The computations were realised with a real set of bank branches of one of
the Czech commercial banks.

For the entire collection see [Zbl 1175.90008].

For the entire collection see [Zbl 1175.90008].

##### MSC:

90B50 | Management decision making, including multiple objectives |