نتایج جستجو برای: optimistic efficiency interval
تعداد نتایج: 590009 فیلتر نتایج به سال:
one of the most popular approaches to measuring productivity changes is based on using malmquist productivity indexes. in this paper we propose a method for obtaining interval malmquist productivity index (impi). the classical dea models have been before used for measuring the malmquist productivity index. the current article extends dea models for measuring the interval malmquist productivity ...
In traditional data envelopment analysis (DEA) the uncertainty of inputs and outputs is not considered when evaluating the performance of a unit. In other words, effects of uncertainty on optimality and feasibility of models are ignored. This paper introduces a new model for measuring the efficiency of decision making units (DMUs) having interval inputs and outputs. The proposed model is based ...
Modeling and solving real world problems is one of the most important issues in optimization problems. In this paper, we present an approach to solve Fuzzy Interval Flexible Linear Programming (FIFLP) problems that simultaneously have the interval ambiguity in the matrix of coefficients .In the first step, using the interval problem solving techniques; we transform the fuzzy interval flexible p...
We discuss the relative merits of optimistic and randomized approaches to exploration in reinforcement learning. Optimistic approaches presented in the literature apply an optimistic boost to the value estimate at each state-action pair and select actions that are greedy with respect to the resulting optimistic value function. Randomized approaches sample from among statistically plausible valu...
Data envelopment analysis is a nonparametric method for measuring the performance of a set of decision-making units (DMUs) that consume multiple inputs to produce multiple outputs. Using this approach, the performance of DMUs is measured from both optimistic and pessimistic views. However, their results are very misleading and even contradictory in many cases. Indisputably, different performanc...
in this paper, a new revenue efficiency data envelopment analysis (re-dea) approach is considered for finding the most revenue efficient unit with price uncertainty in both optimistic and pessimistic perspectives. the optimistic and pessimistic perspectives use efficient frontier and inefficient frontier, respectively. an integrated model is introduced to find decision making units (dmus) that ...
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 disttribution function of the imprecise variable. We take into account only the minimum and the maximum values of each imprecise variable. Two frontiers are cons...
By using the Double Frontiers Criteria, Hurwicz succeeded to achieve The Most Productive Scale Size of decision making units. This Double frontiers criteria was achieved by using two models of “CCR” in optimistic viewpoint in input form and the “CCR” model in pessimistic viewpoint in input form. In this paper, we intend to find a criteria for Double frontiers of super efficiency by using two mo...
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...
Abstract Data Envelopment Analysis (DEA) can be regarded as a useful management tool to the assessment evaluation of decision making units (DMUs) using multiple inputs to produce multiple outputs. In some cases, to evaluate the efficiency having imprecise inputs and outputs such as fuzzy or interval data the efficiency of DMUs won’t be exact as well. Most researches have been conducted were bas...
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