data envelopment analysis (dea) has been widely studied in the literature since its inception with charnes, cooper and rhodes work in 1978. the methodology behind the classical dea method is to determine how much improvements in the outputs (inputs) dimensions is necessary in order to render them efficient. one of the underlying assumptions of this methodology is that the units consume and prod...

This paper proposes the macro model and micro model for the efficiency evaluation of data warehouses (DWH), and introduces Fuzzy Data Envelopment Analysis (FDEA) and Data Envelopment Analysis (DEA) to comprehensively assess DWH efficiency. FDEA can determine the efficiencies of data warehouses with multiple input / output variables, and also resolve the problem that standard DEA cannot handle w...

Department of Industrial Engineering, Khajeh Nasir Toosi University, Tehran, Iran b Louvain School of Management, Center of Operations Research and Econometrics (CORE), Universite Catholique de Louvain, 34 Voie du Roman Pays, B-1348 Louvain-le-Neuve, Belgium Management Department, Lindback Distinguished Chair of Information Systems, La Salle University, Philadelphia, PA 19141, USA Department of...

Some of the parameters in issues of the reality world are uncertainty. One of the uncertain problems with the qualitative parameters is economic problems such as bankruptcy problem. In this case, there is a probability of dealing with imprecise concepts including the intervals regarding the official’s viewpoint, organizations’ managers. Accordingly, this article uses the concepts of data envelo...

Conventional data envelopment analysis (DEA) for measuring the relative efficiency of a set of decisionmaking units (DMUs) requires the observations to have precise values. When observations are imprecise and represented by interval values, the efficiencies are also expected to reflect interval values. Several methods exist to calculate the interval overall and technical efficiencies, but such ...

Abstract We consider the problem of measuring efficiency decision-making units with a ratio-based model. In this perspective, we introduce framework for robustness analysis that admits both interval and ordinal performances on inputs outputs. The proposed methodology exploits uncertainty related to imprecise data all feasible input/output weight vectors delimited through linear constraints. off...

supplier evaluation and selection is important in supply chain management. this is a typical multiple criteria decision making that consists of both quantitative and qualitative factors. ahp is a proper approach to aid this decision making problem, because of its inherent capacity to handle qualitative and quantitative criteria, but when criteria are dependent this method is not so good. also t...