This paper proposes an innovative procedure of finding efficient facility location–allocation (FLA) schemes, integrating data envelopment analysis (DEA) and a multi-objective programming (MOP) model methodology. FLA decisions provide a basic foundation for designing efficient supply chain network in many practical applications. The procedure proposed in this paper would be applied to the FLA pr...

Data envelopment analysis (DEA) is a common technique in measuring the relative efficiency of a set of decision making units (DMUs) with multiple inputs and multiple outputs. ‎‎Standard DEA models are ‎‎quite limited models‎, ‎in the sense that they do not consider a DMU ‎‎at different times‎. ‎To resolve this problem‎, ‎DEA models with dynamic ‎‎structures have been proposed‎.‎In a recent pape...

The paper develops tools for reconciling diverse measures which characterize the ®nancial performance of the Fortune 500 companies. The technology of data envelopment analysis (DEA) is employed to determine a multi-factor ®nancial performance model which inherently recognizes tradeo€s among various ®nancial measures. This study o€ers an alternative perspective and characterization on the perfor...

Abstract Data Envelopment Analysis (DEA) models give each decision making unit freedom to assign values the input-output weights maximising its efficiency score. However, there is no guarantee that optimal obtained from a DEA model are always positive which poses problem, in both theory and practice. This paper offers new linear programming deal with zero problem without restricting or placing ...

The classification of fuzzy uncertain data is considered one of the most challenging issues in data analysis. In spite of the significance of fuzzy data in mathematical programming, the development of the analytical methods of fuzzy data is slow. Therefore, the current study proposes a new fuzzy data classification method based on fuzzy data envelopment analysis (DEA) which can handle strea...