Energy, due to its increasing usage in various broad areas has been maintained as a vital factor in economic growth and development of societies. Meanwhile, natural gas is considered as one of the most important energy sources. Therefore, the efficiency and the productivity of the gas companies are crucial to be assessed. Numerous examples from industrial multistage processes including internal...

The purpose of this study is to present a complementary modeling approach using data envelopment analysis (DEA) and artificial neural network (ANN) as an adaptive decision support tool in promoting best performance benchmarking and performance modeling. DEA and ANN are combined to take advantages of optimization and prediction capabilities inherent in each method. DEA is used as a preprocessor ...

one of the most important decisions in supply chain network (scn) design is choosing the optimal location for the facilities. the facilities in scn have different efficiency according to their locations. in this paper, efficiency of facilities is added to the supply chain network design by using data envelopment analysis model, and a multi-objective model is presented for the design of efficien...

In this paper, a BCC-DPSO scheduling algorithm is proposed to solve multi-objective optimization problem for task scheduling on Network-on-Chip (NoC). In our proposal, the relative advantage of the solution is evaluated by calculating its efficiency using BCC model in Data Envelopment Analysis (DEA), and the referred-time method is introduced to rank the BCC-efficient solution. Moreover, a sub-...

Data envelopment analysis (DEA) measures the relative efficiency of decision making units (DMUs) with multiple inputs and multiple outputs. DEA-based Malmquist productivity index measures the productivity change over time. We propose a dynamic DEA model involving network structure in each period within the framework a DEA. We have previously published the network DEA (NDEA) and the dynamic DEA ...

Supply chain management is essential for the success of firms and customer satisfaction. In addition, a suitable performance evaluation system is vital to the effective management of the supply chain. Due to the importance of cost management in the supply chain, an approach based on Data Envelopment Analysis (DEA) is proposed in the current study for evaluating the cost efficiency of closed-loo...

Data envelopment analysis (DEA) is a linear programming method for assessing the efficiency and productivity of organizational units called decisionmaking units (DMUs). We propose a new network DEA (NDEA) model for measuring the performance of agility in supply chains. The uncertainty of the input and output data is modeled with linguistic terms parameterized with fuzzy sets. The proposed fuzzy...

Data envelopment analysis (DEA) has been a wildly used powerful method to measure efficiencies of decision making units (DMUs). However, DEA efficiency scores are influenced by uncontrollable factors for respective DMUs. Previous studies attempted separating such factors from DEA scores. Fried et al. [4] proposed a multi-stage data adjustment approach using DEA and a regression model, and sever...

The study presents an empirical analysis of best practice production and cost frontiers for a sample of 94 acute care hospitals by applying Data Envelopment Analysis (DEA) and a regression model, in a two-stage approach. This paper contributes to the DEA and efficiency measurement literatures by adding results from a homogeneous method of partitioning cost efficiency into its allocative (or pri...