فهرس المقالات Common weights

• حرية الوصول المقاله
  • صفحة الملخص
  • نص كامل
  
  1 - Ranking of units by anti-ideal DMU with common weights
  Masoumeh Khanmohammadi Maryam Davaei Far
  Data envelopment analysis (DEA) is a powerful technique for performance evaluation of decision making units (DMUs). One of the main objectives that is followed in performance evaluation is discriminating among efficient DMUs to provide a complete ranking of DMUs. DEA su أکثر

  Data envelopment analysis (DEA) is a powerful technique for performance evaluation of decision making units (DMUs). One of the main objectives that is followed in performance evaluation is discriminating among efficient DMUs to provide a complete ranking of DMUs. DEA successfully divides them into two categories: efficient DMUs and inefficient DMUs. The DMUs in the efficient category have identical efficiency score. But the question that raises here is in evaluation. Where several DMUs have the equal efficiency, which unit performs better and how can we rank these efficient units, Different methods have been presented for ranking the efficient units. In this paper, we propose a method for calculating an efficiency of DMUs by comparing with the bad benchmark line. Our approach obtain common set of weights to create the best efficiency score, such that the amount of DMUs that are efficient is less than that of other models. If we have more than one efficient DMU, we can rank them by the same model and it isn't necessary to use another ranking method. تفاصيل المقالة
• حرية الوصول المقاله
  • صفحة الملخص
  • نص كامل
  
  2 - Finding Common Weights in Two-Stage Network DEA
  Mohammad Reza Mozaffari mehrnoosh khazraei
  In data envelopment analysis (DEA), mul-tiplier and envelopment CCR models eval-uate the decision-making units (DMUs) under optimal conditions. Therefore, the best prices are allocated to the inputs and outputs. Thus, if a given DMU was not efficient under optimal condi أکثر

  In data envelopment analysis (DEA), mul-tiplier and envelopment CCR models eval-uate the decision-making units (DMUs) under optimal conditions. Therefore, the best prices are allocated to the inputs and outputs. Thus, if a given DMU was not efficient under optimal conditions, it would not be considered efficient by any other models. In the current study, using common weights in DEA, a number of de-cision-making units are evaluated under the same conditions, and a number of two-stage network DEA models are proposed within the framework of multi-objective linear programming (MOLP) for finding common weights. Furthermore, using the infinity norm, common weight sets are de-termined in two-stage network models with MOLP structures. تفاصيل المقالة
• حرية الوصول المقاله
  • صفحة الملخص
  • نص كامل
  
  3 - Finding common weights in DEA using a compromise solution approach
  Masomeh Abbasi Abbas Ghomashi Saeed Shahghobadi
  10.30495/ijdea.2022.68441.1165
  The weights generated by the common weights approach provide a common criterion for ranking the decision-making units (DMUs) in data envelopment analysis (DEA). Existing common weights models in DEA are either very complicated or unable to produce a full ranking for DMU أکثر

  The weights generated by the common weights approach provide a common criterion for ranking the decision-making units (DMUs) in data envelopment analysis (DEA). Existing common weights models in DEA are either very complicated or unable to produce a full ranking for DMUs. This paper proposes a new compromise solution model to seek a common set of weights for full ranking for DMUs. The maximum inefficiency scores calculated from the standard DEA model are regarded as the anti-ideal solution for the DMUs to avoid. A common set of weights that produces the vector of inefficiency scores for the DMUs furthest to the anti-ideal solution is sought. The discrimination power of the new model is tested using two numerical examples and its potential application for fully ranking DMUs is illustrated. تفاصيل المقالة
• حرية الوصول المقاله
  • صفحة الملخص
  • نص كامل
  
  4 - Measuring congestion in data envelopment analysis with common weights
  A.A. Noura E. Hoseini
  تفاصيل المقالة
• حرية الوصول المقاله
  • صفحة الملخص
  • نص كامل
  
  5 - Common weights for the evaluation of decision-making units with nonlinear virtual inputs and outputs
  S. Borzoei M. Zohrehbandian
  In this paper, by investigating the common weights concept and DEA models with nonlinear virtualinputs/outputs, we introduce a model for evaluating the decision making units with nonlinear virtual inputs and outputs based on the common weights.

  In this paper, by investigating the common weights concept and DEA models with nonlinear virtualinputs/outputs, we introduce a model for evaluating the decision making units with nonlinear virtual inputs and outputs based on the common weights. تفاصيل المقالة
• حرية الوصول المقاله
  • صفحة الملخص
  • نص كامل
  
  6 - Upgrading inefficient decision making units (with negative data) towards common weights (using DEA)
  حسین عباسیان
  The main purpose of this paper is to upgrade and improve inefficient units by common weights obtained from all units studied. In fact, we consider the common weight vector as the direction in which inefficient units rise. The methodology of this research is to consider أکثر

  The main purpose of this paper is to upgrade and improve inefficient units by common weights obtained from all units studied. In fact, we consider the common weight vector as the direction in which inefficient units rise. The methodology of this research is to consider the semi-essential radial model and we want to use the duality of this model to find the common weights of inputs and outputs, some of which are negative. For this purpose, we present a multi-objective problem of generating common weights and use ideal programming to solve it, which leads to the production of a nonlinear problem, which for this particular problem, by a linearization method, is called We turn a linear programming problem. Since the necessary and sufficient condition for the boundary of the semi-essential radial model in the nature of input (output) is that there is an input (output) with at least one positive value, so we observe this condition here. Finally, we will explain our method with an example and the remarkable thing about the promotion method in the present study is that negative data is promoted and improved as negative data. تفاصيل المقالة
• حرية الوصول المقاله
  • صفحة الملخص
  • نص كامل
  
  7 - Portfolio Selection using Data Envelopment Analysis with common weights
  A. علینژاد M. Zohrebandian ف. دهدار
  The stock evaluation process plays an important role in portfolio selectionbecause it is the prerequisite for investment and directly influences on the stockallocation. This paper presents a methodology based on Data EnvelopmentAnalysis for portfolio selection, decision أکثر

  The stock evaluation process plays an important role in portfolio selectionbecause it is the prerequisite for investment and directly influences on the stockallocation. This paper presents a methodology based on Data EnvelopmentAnalysis for portfolio selection, decision making units which can be stocks orother financial assets. First, DMUs efficiencies are computed based oninput/output common weights, and then the generation of a portfolio is carried outby a mathematical model. Finally the methodology is illustrated numerically onthe market of Iran stock exchange. تفاصيل المقالة
• حرية الوصول المقاله
  • صفحة الملخص
  • نص كامل
  
  8 - An MCDM-DEA approach for technology selection
  A Alinezhad A Makui R Kiani Mavi M Zohrehbandian
  Technology selection is an important part of management of technology. Recently Karsak and Ahiska (2005) proposed a novel common weight multiple criteria decision making (MCDM) methodology for selection of the best Advanced Manufacturing Technology (AMT) candidates base أکثر

  Technology selection is an important part of management of technology. Recently Karsak and Ahiska (2005) proposed a novel common weight multiple criteria decision making (MCDM) methodology for selection of the best Advanced Manufacturing Technology (AMT) candidates based on a number of attributes. However, Amin et al. (2006), by means of a numerical example demonstrated the convergence difficulty of the Karsak and Ahiska algorithms, and then introduced an improvement model to rectify that running problem. This paper presents an MCDM-DEA methodology in order to evaluate the relative efficiency of AMTs with respect to multiple outputs and a single exact input. Using displaced ideal methodology, a practical common weight is developed and its robustness and discriminating power are illustrated via a previously reported robot evaluation problem by comparing the ranking obtained by the proposed MCDM framework with that obtained by a data envelopment analysis (DEA) classic model. تفاصيل المقالة
• حرية الوصول المقاله
  • صفحة الملخص
  • نص كامل
  
  9 - Two methods to obtain preferred efficiency for negative data (IS)
  Hossein Abbasiyan mohamadjafar doostideilami
  10.30495/ijm2c.2023.1952616.1246
  The original DEA models were applicable only to technologies characterized by positive inputs/outputs. We consider the interval scale (IS) variables especially when the IS variable is a difference of two different variables (like sales etc.) have been used as inputs and أکثر

  The original DEA models were applicable only to technologies characterized by positive inputs/outputs. We consider the interval scale (IS) variables especially when the IS variable is a difference of two different variables (like sales etc.) have been used as inputs and/or outputs. We measure Preferred Efficiency (PE) in Data Envelopment Analysis (DEA) with negative data when these data derived from IS variables. The PE is an efficiency concept that takes into account the decision maker’s (DM) preferences. We search the Most Preferred combination of inputs and outputs of Decision Making Units (DMUs) which are efficient in DEA. Also, we approximate indifference contour of the unknown Preferred Function (PF) at Most Preference Solution (MPS) with supporting hyperplane on PPS at MPS. We propose a way to obtain this the supporting hyperplane and also assume this the hyperplane is tangent on the indifference contour of PF. We use from the radial DEA problems with Variable Returns to Scale (VRS) (BCC models) at the combination orientation (both outputs are maximized and inputs are minimized). Also, We decompose each IS variable into two Ratio Scale (RS) variables and then utilizing from a compromise solution approach generate Common Weights (CW) for the decomposed input/output variables. In other to, we will introduce an MOLP model which its objective functions are input/output variables subject to the defining constraints of production possibility set (PPS) of DEA models. Lastly, the procedure and the resulting PE scores are applicable to solving practical problems by the mentioned models. تفاصيل المقالة