51 research outputs found

    Malmquist Productivity Index Using Two-Stage DEA Model in Heart Hospitals

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    International audienceHeart patients displays several symptoms and it is hard to point them. Data envelopment analysis (DEA) provides a comparative efficiency degree for each decision-making units (DMUs) with several inputs and outputs. Evaluating of hospitals is one of the major applications in DEA. In this study, a comparison of additive model with standard input oriented and output oriented Malmquist productivity index (MPI) are used. The MPI is calculated to measure productivity growth relative to a reference technology. Two primary subjects are addressed in computation of MPI growth. What are generally referred to as a "catching-up" effect or technical efficiency change (TEC) and a "frontier shift" effect or technological change (TC). The data covers a six-year span from 2011 to 2016 for 15 local heart hospitals. Two inputs, one intermediate element and two outputs are chosen in two-stage model and these factors reflect the main function of hospitals. Conversion of two-stage to single stage model is introduced. This model is proposed to fix the efficiency of a two-stage process, and avoid the dependence to various weights. Finally, the results indicated that geometry average of MPI in input oriented pure technical efficiency (PTE) in the tenth Hospital (2.1517) is introduced as the highest performance hospital with highest productivity growth

    Performance Evaluation of Supply Chain under Decentralized Organization Mechanism

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    Abstract Nowadays among many evaluation methods, data envelopment analysis has widely used to evaluate the relative performance of a set of Decision Making Units (DMUs). Data Envelopment Analysis (DEA(is a mathematical tool for evaluating the relative efficiency of a set Decision Making Units (DMUs), with multiple inputs and outputs. Traditional DEA models treat with each DMU as a “black box" thus, the performance measurement may be not effective. So, there are necessities for network DEA models. The objective of this paper is to propose a new network DEA model for measuring the efficiency of two- supplier and one manufacturer chains under the decentralized organization mechanism. In this mechanism, each section of supply chain is controlled under unique decision maker with his/her own interest. We proposed that, in comparison with CCR model, for the supply chain under decentralized organization mechanism, it is not appropriate to ignore the internal structure and treat as a “black box”, while there is more than one decision maker with different interests. Furthermore, the relation between the supply chain efficiency and division efficiency is investigated. Numerical example demonstrates the application of the proposed model

    Optimization of the Allowable Speed on Iran’s Freeways to Reduce Violations and Accidents, Using Zero-Truncated Poisson Regression Model

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    Countries from all over the world including Iran, consider different maximum allowable speeds to control and maintain traffic safety on their freeways, but these actions have not been successful even with the police surveillance. Even though speeding is not the only cause of accidents, past studies indicate that speed plays a vital role in such events. Since respecting the speed limits have not prevented driving violations and traffic accidents, there’s doubt among decision-makers, about the applicability and safety of these legal speed limits in different weather and traffic conditions. They think perhaps there is a need for an optimized and safe speed after doing required studies. Even in the police instructions and notifications in unfavorable weather conditions, the word “safe speed” is used more than the “legal speed” and its limit is not mentioned and its determination is assigned to drivers according to their mental and physical conditions, type of vehicle, and the weather condition. This matter leads to uncertainty for drivers in selecting the right speed.This research is intended to achieve a safe and optimized speed for freeways in Iran, by considering a reasonable adjustment which is acceptable by the drivers so that a substantial decrease in driving violations and accidents could be observed. This work is done by using models developed for predicting violations and accidents on Iran’s freeways. The results indicate that by reducing the allowable speed of freeways from 125km/h to 105km/h, a 48% and 23% reduction of violations and traffic accidents could be achieved

    Sensitivity Analysis of TOPSIS Technique: The Results of Change in the Weight of One Attribute on the Final Ranking of Alternatives

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    Most of data in Multi-attribute decision making (MADM) problems are changeable rather than constant and stable. Therefore, sensitivity analysis after problem solving can effectively contribute to making accurate decisions. In this paper, we offer a new method for sensitivity analysis in multi-attribute decision making problems in which if the weights of one attribute changes, then we can determine changes in the results of the problem. These changes involve changes in the weight of other attributes and the change in the final rank of alternatives. This analysis was conducted for Technique for order-preference by similarity to ideal solution (TOPSIS) technique, one of the most frequently used multi-attribute decision making techniques, and the formulas were obtained. The paper continues with a numerical example and at last conclusions and suggestions for future researches are offered

    Sensitivity Analysis in the QUALIFLEX and VIKOR Methods

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    The sensitivity analysis for multi-attribute decision making (MADM) problems is important for two reasons: First, the decision matrix as the source of the results of a decision problem is inaccurate because it sorts the alternatives in each criterion inaccurately. Second, the decision maker may change his opinions in a time period because of changes in the importance of the criteria and in the policy of the organization over time. This in turn makes problem solving really time-consuming. Therefore, the best solution is to do sensitivity analysis.In this regard, this paper considers a sensitivity analysis in the QUALIFLEX method which is a compromise ranking method used for multi-criteria decision making (MCDM)

    Malmquist Productivity Index Using Two-stage DEA Model in Heart Hospitals

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    Abstract Heart patients displays several symptoms and it is hard to point them. Data envelopment analysis (DEA) provides a comparative efficiency degree for each decision-making units (DMUs) with several inputs and outputs. Evaluating of hospitals is one of the major applications in DEA. In this study, a comparison of additive model with standard input oriented and output oriented Malmquist productivity index (MPI) are used. The MPI is calculated to measure productivity growth relative to a reference technology. Two primary subjects are addressed in computation of MPI growth. What are generally referred to as a “catching-up” effect or technical efficiency change (TEC) and a “frontier shift” effect or technological change (TC). The data covers a six-year span from 2011 to 2016 for 15 local heart hospitals. Two inputs, one intermediate element and two outputs are chosen in two-stage model and these factors reflect the main function of hospitals. Conversion of two-stage to single-stage model is introduced. This model is proposed to fix the efficiency of a two-stage process, and avoid the dependence to various weights. Finally, the results indicated that geometry average of MPI in input oriented pure technical efficiency (PTE) in the tenth Hospital (2.1517) is introduced as the highest performance hospital with highest productivity growth

    A Fuzzy Goal Programming Model for Efficient Portfolio Selection.

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    This paper considers a multi-objective portfolio selection problem imposed by gaining of portfolio, divided yield and risk control in an ambiguous investment environment, in which the return and risk are characterized by probabilistic numbers. Based on the theory of possibility, a new multi-objective portfolio optimization model with gaining of portfolio, divided yield and risk control is proposed and then the proposed model is solved as a fuzzy goal programming model to fulfill aspiration level of each objective. Furthermore, numerical example of efficient portfolio selection is provided to illustrate that proposed model is versatile enough to be applicable to various unexpected conditions. This paper considers a multi-objective portfolio selection problem imposed by gaining of portfolio, divided yield and risk control in an ambiguous investment environment, in which the return and risk are characterized by probabilistic numbers. Based on the theory of possibility, a new multi-objective portfolio optimization model with gaining of portfolio, divided yield and risk control is proposed and then the proposed model is solved as a fuzzy goal programming model to fulfill aspiration level of each objective. Furthermore, numerical example of efficient portfolio selection is provided to illustrate that proposed model is versatile enough to be applicable to various unexpected conditions

    A multi-objective evolutionary approach for integrated production-distribution planning problem in a supply chain network

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    Integrated production-distribution planning (PDP) is one of the most important approaches in supply chain networks. We consider a supply chain network (SCN) to consist of multi suppliers, plants, distribution centers (DCs), and retailers. A bi-objective mixed integer linear programming model for integrating production-distribution designed here aim to simultaneously minimize total net costs in supply chain and transfer time of products for retailers. From different terms of evolutionary computations, this paper proposes a Pareto-based meta-heuristic algorithm called multi-objective simulated annealing (MOSA) to solve the problem. To validate the results obtained, a popular algorithm namely non-dominated sorting genetic algorithm (NSGA-II) is utilized as well. Since the solution-quality of proposed meta-heuristic algorithm severely depends on their parameters, the Taguchi method is utilized to calibrate the parameters of the proposed algorithm. Finally, in order to prove the validity of the proposed model, a numerical example is solved and conclusions are discussed

    Sensitivity Analysis of Simple Additive Weighting Method (SAW): The Results of Change in the Weight of One Attribute on the Final Ranking of Alternatives

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    Most of data in a multi-attribute decision making (MADM) problem are unstable and changeable, then sensitivity analysis after problem solving can effectively contribute to making accurate decisions. This paper provides a new method for sensitivity analysis of MADM problems so that by using it and changing the weights of attributes, one can determine changes in the final results of a decision making problem. This analysis applied for SAW technique, one of the most used multi-attribute decision making techniques, and the formulas are obtained

    A Model for Allocating Orders to Suppliers in Case of Quantity Discounts

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    One of the most important activities in the management of input items of a company is focusing on the process of purchasing, supplier selection and allocating order to suppliers. Decisions about supplier selection due to simultaneously taking inconsistent and diverse issues into account in a wide range of strategic to operational factors, and from quantitative to qualitative criteria will be complex by nature. In order to select the best suppliers it is necessary to make a trade-off between these tangible and intangible factors some of which may conflict. When business volume discounts exist, this problem becomes more complicated. In this paper a multi-objective model for order allocation under volume discount conditions is presented. In this context, suppliers offer price discounts on total business volume. A solution methodology is presented to solve the multi-objective model, and the model is illustrated using a numerical example. Studying various combinations of constraints such as capacity, timely delivery, disadvantages and cost, taking into account quantity discounts, considering the weight of the suppliers in order allocation and integration of these cases with each other, have made the current research quite unique
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