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Developing an Output‐Oriented Super Slacks‐Based Measure Model with an Application to Third‐Party Reverse Logistics Providers
Author(s) -
Azadi Majid,
Saen Reza Farzipoor
Publication year - 2011
Publication title -
journal of multi‐criteria decision analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.462
H-Index - 47
eISSN - 1099-1360
pISSN - 1057-9214
DOI - 10.1002/mcda.483
Subject(s) - outsourcing , data envelopment analysis , measure (data warehouse) , computer science , mathematical optimization , quadratic equation , sensitivity (control systems) , operations research , econometrics , economics , mathematics , data mining , engineering , business , marketing , geometry , electronic engineering
ABSTRACT Outsourcing is an increasingly significant topic pursued via corporations seeking enhanced efficiency. Third‐party reverse logistics involves the employ of external firms to carry out some or all of the firm's logistics activities. Output‐oriented super 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 address uncertainty in data is to replace deterministic data via random variables, leading to chance‐constrained DEA. In this paper, a chance‐constrained output‐oriented super SBM model is developed and also its deterministic equivalent, which is a nonlinear program, is derived. Furthermore, it is shown that the deterministic equivalent of the stochastic output‐oriented super SBM model can be converted into a quadratic program. In addition, sensitivity analysis of the stochastic output‐oriented super SBM model is discussed with respect to changes on parameters. Finally, a numerical example demonstrates the application of the proposed model. Copyright © 2011 John Wiley & Sons, Ltd.