• Journal of the military operations research society of Korea
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• v.36 no.3
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• pp.1-13
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• 2010

DEA method has been widely applied on civilian and defense side for efficiency analysis of organizations and programs(project). For many years Defense Industry, military hospital and military construction parts have been analyzed by using DEA method. In this paper we review and propose a method of warship evaluation through DEA method. The evaluation method proposed above can provide plenty of proper information for ROC decision, AOA and source selection on weapon acquisition.

• Knowledge Management Research
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• v.13 no.3
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• pp.55-77
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• 2012

Selecting promising technology is becoming more and more difficult due to the increased number and complexity. In this study, we propose hybrid AHP/DEA-AR method and hybrid AHP/DEA-AR-G method to evaluate efficiency of technology alternatives based on ordinal rating data collected through survey to technology experts in a certain field and select efficient technology alternative as promising technology. The proposed method normalizes rating data and uses AHP to derive weights to improve the credibility of analysis, then in order to avoid basic DEA models' problems, use DEA-AR and DEA-AR-G to evaluate efficiency of technology alternatives. In this study, we applied the proposed methods to clean technology and compared with the basic DEA models. According to the result of the comparison, we can find that the both proposed methods are excellent in confirming most efficient technology, and hybrid AHP/DEA-AR method is much easier to use in the process of technology selection.

• Korean Management Science Review
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• v.23 no.2
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• pp.93-107
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• 2006

This paper attempts to improve the typical DEA model that is often used as a performance evaluation method for service firms. The after-sales service system in a Korean electronic company is chosen as a sample case. The performance evaluation method currently practiced in the firm was reviewed and some critical issues of the current method were discussed. DEA model would be considered a solution for solving those Issues. However, typical DEA models has various drawbacks in determining the weights over evaluation criteria. Proposed is the priority-constrained DEA model that accommodates the strategic Importance of each evaluation criterion. The results of the proposed model are compared with those of typical DEA models. It is shown that the priority-constrained DEA model is superior to the others in terms of evaluation quality.

• The Journal of Fisheries Business Administration
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• v.41 no.3
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• pp.45-58
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• 2010

This study estimated the technical efficiency of coastal composite fishery in Korea by using the data envelopment analysis (DEA) and the stochastic frontier analysis (SFA) methods, and the results on the respective method were compared. In the DEA method, the constant returns to scale (CRS) and the variable returns to scale (VRS) output-oriented DEA models were separated and technical efficiencies were estimated, respectively. The average estimated value of technical efficiency by the SFA method (0.633) was found to be lower than that by the VRS-DEA method (0.738), while it was higher than that by the CRS-DEA method (0.479). It was found that strong correlation exists between the SFA method and the VRS-DEA method. The method which can utilize both methods in mutually complementing way for the estimation of technical efficiency was also considered.

• Journal of Korea Port Economic Association
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• v.17 no.1
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• pp.27-51
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• 2001

The purpose of this paper is to investigate the productive efficiency of world container ports by using the DEA (Data Envelopment Analysis) method and raw data from previous research in measuring the international competitiveness of world container ports. Ports have to cope with rapid changes in shipping environments. In order for a port to compete in the global market, it must provide port services promptly and accurately. Basically, there are two approaches to measuring the international competitiveness of a container port. First, there is the traditional productivity analysis method, which analyzes productivity based on the container port's facilities (efficiency, selectivity, land availability), and by its general capacity (handling ability, storage capacity, terminal productivity). Second there is multi-attribute utility analysis, which considers several elements including the reasons for selecting particular container ports and factors determining international competitiveness. This paper follows the first method (traditional productivity analysis) and extends the limitation of previous studies by using the DEA method newly, and suggesting: the relative productive efficiency of container ports. The main results of this paper are as follows: First, the results of the DEA analysis in terms of world container ports matches that of a previous study (Jun et al., 1993) at a level of 35%. The low ratio is due to the constrained set of input-output elements, the result of only twenty container ports being analyzed in this paper. Second, the result of the DEA analysis in terms of North-East Asia's container ports matches with that of a previous study (Ha, 1996) at a level of 100 percent. Therefore we can conclude that the DEA analysis is the best measurement method for international competitiveness. Policy implications for this study are as follows: First, when port authorities want to measure the international competition power of container ports and enhance their productive efficiency, they should consider the traditional method and newly introduce the DEA method. Second, according to the analysis results of the DEA method, pen authorities should recommend benchmarking ports as reference ports in order to enhance the productive efficiency of container ports that show an efficiency score of below 1.

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.2
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• pp.53-68
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• 1999

This paper presents a nonparametric method to test if the mean difference of DEA efficiency estimates between two groups statistically exists. A proposed method employs a bootstrapping approach to generation BCC efficiency estimates through Monte Carlo simulation resampling process. For the purpose of demonstration, we empirically apply the proposed method to the korean bank industry and compare its result with the result by the traditional deterministic DEA method. The nonparametric statistical hypothesis testing procedure in this study, which considers not only stochastic variability of the DEA data, but also random radial deviations off the efficient frontier, serves as a useful tool for dbjectively evaluating whether the mean difference of DEA efficiency estimates between groups is statistically significant.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.1 no.1
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• pp.83-90
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• 2000

DEA is a newly developed analyzing tool to measure efficiency evaluation of decision making units (DMU). It compares DMU by radial Projection on the efficient frontier. The purpose of this study is to show reference point approach used for searching solution in multiple objective linear Programming can be usefully used to determine flexible efficient frontier of each DMU In reference point approach, the minimization of ASF Produces an efficient points in frontier and enhances the usefulness of DEA by Providing flexibility in DEA and optimally allocating resources to DMU. Various DEA models can be supported by reference point method by changing the projection direction in order to choose the targets units, standards costs and management benching-marking.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.2
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• pp.1-6
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• 2006

This study proposes a new approach which combines Data Envelopment Analysis(DEA) and the Analytic Hierarchy Process(AHP) techniques to effectively evaluate Decision Making Units(DMUs). While DEA evaluates a quantitative data set, employs linear programming to obtain input and output weights and ranks the performance of DMUs, AHP evaluates the qualitative data retrieved from expert opinions and other managerial information in specifying weights. The objective of this research is to design a decision support process for managers to incorporate positive aspects of DEA's absolute numerical evaluations and AHP's human preference structure values. It is believed that a pragmatic manager will be more receptive to the results that include subjective opinions incorporated into the evaluation of the efficiency of each DMU efficiency. The WPDEA method provides better discrimination than the DEA method by reducing the number of efficient units.

• Journal of the Korean Geotechnical Society
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• v.35 no.4
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• pp.27-35
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• 2019

This study confirmed the applicability to the field of geotechnical engineering for relatively complicated space and many target design variables in back analysis. The Sharan's equation and the Blum's method were used for the tunnel field and the retaining wall as a model for the multi-variate problem of geotechnical engineering. Optimization methods are generally divided into a deterministic method and a stochastic method. In this study, Simulated Annealing Method (SA) was selected as a deterministic method and Differential Evolution Algorithm (DEA) and Particle Swarm Optimization Method (PSO) were selected as stochastic methods. The three selected optimization methods were compared by applying a multi-variate model. The problem of deterministic method has been confirmed in the multi-variate back analysis of geotechnical engineering, and the superiority of DEA can be confirmed. DEA showed an average error rate of 3.12% for Sharan's solution and 2.23% for Blum's problem. The iteration number of DEA was confirmed to be smaller than the other two optimization methods. SA was confirmed to be 117.39~167.13 times higher than DEA and PSO was confirmed to be 2.43~6.91 times higher than DEA. Applying a DEA to the multi-variate back analysis of geotechnical problems can be expected to improve computational speed and accuracy.

• Applied Chemistry for Engineering
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• v.33 no.6
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• pp.646-652
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• 2022

The dead-end anode (DEA) system is a method that closes the anode outlet and supplies fuel by pressure. The DEA method could improve fuel usage and power efficiency through system simplification. However, flooding occurs due to water and nitrogen back diffusion from the cathode to the anode during the DEA operation. Flooding is a cause of decreased fuel cell performance and electrode degradation. Therefore, tthe structure and components of polymer electrolyte membrane fuel cell (PEMFC) should be optimized to prevent anode flooding during DEA operation. In this study, the effect of a porous flow field with metal foam on fuel cell performance and fuel efficiency improvement was investigated in the DEA system. As a result, fuel cell performance and purge interval were improved by effective water management with a porous flow field at the cathode, and it was confirmed that cathode flow field structure affects water back-diffusion. On the other hand, the effect of the porous flow field at the anode on fuel cell performance was insignificant. Purge interval was affected by metal foam properties and shown stable performance with large cell size metal foam in the DEA system.