Multi-criteria decision-making (MCDM) issues related to hydrogen energy usually involve weight consideration of evaluation criteria, ambiguous information provided by experts, and lacking or incomplete information. Conventionally, the MCDM calculation method cannot effectively simultaneously process To address this issue, study proposed a novel general data envelopment analysis (DEA)-based appr...

data envelopment analysis is a nonparametric technique checking efficiency of dmus using math programming. in conventional dea, it has been assumed that the status of each measure is clearly known as either input or output. kao and hwang (2008) developed a data envelopment analysis (dea) approach for measuring efficiency of decision processes which can be divided into two stages. the first stag...

-In recent years, with the expansion of existing institutions as well as the establishment of new ones, higher education institutions have suffered the problem of declining available resources. Each university must assess the performance of its critical business units to measure effectiveness and efficiency. The purpose of this study is to assess university performance. In this study, we apply ...

Although crisp data are fundamentally indispensable for determining the profit Malmquist productivity index (MPI), the observed values in real-world problems are often imprecise or vague. These imprecise or vague data can be suitably characterized with fuzzy and interval methods. In this paper, we reformulate the conventional profit MPI problem as an imprecise data envelopment analysis (DEA) pr...

  A data envelopment analysis (DEA) method can be regarded as a useful management tool to evaluate decision making units (DMUs) using multiple inputs and outputs. In some cases, we face with imprecise inputs and outputs, such as fuzzy or interval data, so the efficiency of DMUs will not be exact. Most researchers have been interested in getting efficiency and ranking DMUs recently. Models of th...

Performance evaluation plays an important role in determining faults and difficulties of any supply chain as well as attempting to increase capabilities and improve activities. Data envelopment analysis (DEA), as a non-parametric method, has been one of the most important and significant management tools for measuring output or efficiency. In fact, in a real evaluation problem input and output ...

Interval DEA frontiers are here used in situations where one input or output is subject to uncertainty in its measurement and is presented as an interval data. We built an efficient frontier without any assumption about the probability distribution function of the imprecise variable. We take into account only the minimum and the maximum values of each imprecise variable. Two frontiers are const...

At present, bid evaluation in China mainly adopts the method of traditional comprehensive scoring. And the method of analytic hierarchy process or fuzzy synthetic assessment is also in common use. However, those methods have their own weaknesses, e.g., having a strong subjectivity, lacking in analysis of quantitative indicators, and being unable to reflect the defects of the bidders and reasons...

in this paper, by introducing two virtual decision-making units (dmus) called ideal dmu (idmu) and anti-ideal dmu (admu) with fuzzy inputs-outputs, the efficiency evaluation of dmus are done by fuzzy data envelopment analysis (fdea). therefore, we evaluate dmus from the perspective of the best and worst possible relative efficiency. for each dmu two efficiencies are calculated while inputs and ...