perfomance management
Esmaeil Keshavarz; abbas shoul; Ali Fallah Tafti
Abstract
Data Envelopment Analysis (DEA) is an approach based on mathematical programming for the relative evaluation of decision-making units treated as similar yet distinct production systems. In this approach, the performance of each unit is characterized by describing the transformation of specific inputs ...
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Data Envelopment Analysis (DEA) is an approach based on mathematical programming for the relative evaluation of decision-making units treated as similar yet distinct production systems. In this approach, the performance of each unit is characterized by describing the transformation of specific inputs into specific outputs. Traditional DEA models assume that the role of each performance factor is clearly defined. However, in some real-world problems, certain factors might be identified as dual-role factors depending on the evaluation nature or the decision-makers' perspective. These factors can play the role of both input and output, or even be considered neutral in assessing the units' performance. In the current paper, to determine the status of dual-role factors and calculate the efficiency of DMUs, two new linear programming models, based on the concept of deviation in the efficiency constraint and a common set of weights, are suggested. The main advantages of the proposed models are significantly reducing the computations and iterations required to solve the model, and involving all DMUs to determine the role of factors. To assess the performance of the proposed models, a data set for the evaluation of eighteen suppliers in the presence of two inputs, three outputs, and two dual-role factors has been employed. The obtained results showed that, compared to other models, the proposed models are computationally more efficient, and the role determination and evaluation of the units, based on the obtained weights from these models, are better aligned with the expectations of decision-makers
Abbas Shoul; Esmaeil Keshavarz
Abstract
In the present research, Time-Cost-Quality trade off problem is formulated and solved, from a new point of view. To this end, quality is defined as a function of time and cost, then by defining the project’s quality as minimum value of quality of activities and regarding predecessor relations between ...
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In the present research, Time-Cost-Quality trade off problem is formulated and solved, from a new point of view. To this end, quality is defined as a function of time and cost, then by defining the project’s quality as minimum value of quality of activities and regarding predecessor relations between activities, a tri-objective programming model is formulated to trade off the time, cost and quality. In order to solve the problem, objective functions of time and cost described as fuzzy goals and a fuzzy decision-making methodology has been used to reformulate the proposed tri-objective model to a single-objective model. Producing a final solution, instead of a set of Pareto efficient solutions, is one of the advantages of proposed method, which prevents decision maker from confusion. In order to describe performance and show the potential applicability of proposed methodology, a time-cost-quality trade-off problem for a project with real data from Organization for Renovating, Developing and Equipping Schools of Kerman province is solved. Finally, in order to validate the proposed model and method, a parametric analysis, which systematically varies the main parameters of model, is employed.
