Izvorni znanstveni članak
https://doi.org/10.17535/crorr.2017.0025
An input relaxation model for evaluating congestion in fuzzy DEA
Hooshang Kheirollahi
; Kurdistan University of Medical Sciences, Sanandaj, Iran
Peyman Hessari
; Department of Mathematical and Statistical Sciences, University of Alberta 116 St. and 85 Ave., Edmonton, AB, T6G 2G1, Canada
Vincent Charles
orcid.org/0000-0001-8943-5681
; CENTRUM Católica Graduate Business School, PUCP Calle Daniel Alomía Robles 125 - 129, Los Álamos de Monterrico, Santiago de Surco, Lima 33, Peru
Rasoul Chawshini
; Kurdestan Electricity Power Distribution Company, Janbazan St., Sanandaj, Kurdistan Province, Iran
Sažetak
This paper develops a BCC input relaxation model for identifying input congestion as a severe form of inefficiency of decision-making units in fuzzy data envelopment analysis. The possibility approach is presented to obtain the models equivalent to fuzzy models. We use a one-model approach to determine input congestion based on the BCC input relaxation model. A numerical example is given to illustrate the proposed model and identify the congestion with precise and imprecise data. The proposed model is also used to determine the congestion in 16 hospitals using four fuzzy inputs and two fuzzy outputs with a symmetrical triangular membership function.
Ključne riječi
fuzzy data envelopment analysis (FDEA); congestion; relaxed inputs
Hrčak ID:
193539
URI
Datum izdavanja:
30.12.2017.
Posjeta: 1.114 *