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The problem of ranking Decision Making Units (DMUs) in Data Envelopment Analysis DEAA) has been widely studied in the literature.
To conclude, cost comparison information (M = 4.79; SD = 1.78) had the lowest impact on ranking decision, while information on CCS (M = 5.68; SD = 5.61), types of power plants (M = 5.6; SD = 1.58), and pollution comparison (M = 5.42; SD = 1.54) had the highest impact.
The CDF lines for alternatives in Fig. 1 crossing each other and there is no clear ranking decision can be produced for the Decision Makers under different RAC.
A ranking decision making technique Elimination and Choice Expressing the Reality (ELECTRE III) is applied to the Pareto-front so as to obtain one optimal solution.
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The robust DEA model proposed is aimed at ranking decision-making units (DMUs) based on their sensitivity analysis within the given set of scenarios, considering both feasibility and optimality factors in the objective function.
In this research SWARA produces criteria weights and COPRAS will rank decision alternatives.
MODSS module provides different ranked decisions and evaluates its impact on the operation.
This section documents the methodological steps of a hybrid decision support model for ranking the decision alternatives under MCDA environment.
After conducting an investigation, the company discovered it had left the ranking decisions up to low-level contractors.
Further difficulties may occur in the case of partnerships between different Local Action Groups, such as disagreement about whether a given factor is a Strength or a Weakness, lack of information about the relationships between Strength and a Weakness factors and decision alternatives, as well as impossibility of ranking the decision alternatives.
In many applications, ranking of decision making units (DMUs) is a problematic technical task procedure to decision makers in data envelopment analysis (DEA), especially when there are extremely efficient DMUs.
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