TY - JOUR
T1 - Developing a nondiscretionary slacks-based measure model for supplier selection in the presence of stochastic data
AU - Azadi, Majid
AU - Saen, Reza Farzipoor
PY - 2012
Y1 - 2012
N2 - Supplier selection has a strategic importance for every company. Nondiscretionary Slacks-based Measure (SBM) model is one of the models in Data Envelopment Analysis (DEA). In many real world applications, data are often stochastic. A successful approach to the address uncertainty in data is to replace deterministic data via random variables, leading to Chance-con strained DEA (CCDEA). In this study, the concept of chance-constrained programming approach is used to develop nondiscretionary SBM model in the presence of stochastic data and also its deterministic equivalent which is a nonlinear program is derived. Furthermore, it is shown that the deterministic equivalent of the stochastic nondiscretionary SBM model can be converted into a quadratic program. Finally, a numerical example demonstrates the application of the proposed model.
AB - Supplier selection has a strategic importance for every company. Nondiscretionary Slacks-based Measure (SBM) model is one of the models in Data Envelopment Analysis (DEA). In many real world applications, data are often stochastic. A successful approach to the address uncertainty in data is to replace deterministic data via random variables, leading to Chance-con strained DEA (CCDEA). In this study, the concept of chance-constrained programming approach is used to develop nondiscretionary SBM model in the presence of stochastic data and also its deterministic equivalent which is a nonlinear program is derived. Furthermore, it is shown that the deterministic equivalent of the stochastic nondiscretionary SBM model can be converted into a quadratic program. Finally, a numerical example demonstrates the application of the proposed model.
KW - Chance-constrained data envelopment analysis
KW - Nondiscretionary slacks-bared measure
KW - Quadratic program
KW - Sensitivity analysis
KW - Supplier selection
KW - Supply chain management
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U2 - 10.3923/rjbm.2012.103.120
DO - 10.3923/rjbm.2012.103.120
M3 - Article
AN - SCOPUS:84872190370
SN - 1819-1932
VL - 6
SP - 103
EP - 120
JO - Research Journal of Business Management
JF - Research Journal of Business Management
IS - 4
ER -