49,069 research outputs found

    Using a modified DEA model to estimate the importance of objectives. An application to agricultural economics.

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    This paper shows a connection between Data Envelopment Analysis (DEA) and the methodology proposed by Sumpsi et al. (1997) to estimate the weights of objectives for decision makers in a multiple attribute approach. This connection gives rise to a modified DEA model that allows to estimate not only efficiency measures but also preference weights by radially projecting each unit onto a linear combination of the elements of the payoff matrix (which is obtained by standard multicriteria methods). For users of Multiple Attribute Decision Analysis the basic contribution of this paper is a new interpretation of the methodology by Sumpsi et al. (1997) in terms of efficiency. We also propose a modified procedure to calculate an efficient payoff matrix and a procedure to estimate weights through a radial projection rather than a distance minimization. For DEA users, we provide a modified DEA procedure to calculate preference weights and efficiency measures which does not depend on any observations in the dataset. This methodology has been applied to an agricultural case study in Spain.Multicriteria Decision Making, Goal Programming, Weights, Preferences, Data Envelopment Analysis.

    Extended Topics in the Integration of Data Envelopment Analysis and the Analytic Hierarchy Process in Decision Making.

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    The Analytic Hierarchy Process (AHP) is a procedure, which can only consider relative priorities as estimated by decision-makers. A Data Envelopment Analysis (DEA) model is a data-oriented approach for evaluating the relative efficiency of a group of entities referred to as Decision Making Units (DMUs). This research work integrates and combines positive aspects of AHP\u27s estimated qualitative data and DEA\u27s quantitative data. This combination is accomplished by specifying two variants of the DEA methodology for selection of the best DMU. Initially the priority weights of AHP are integrated with the DEA methodology to provide results that are logic based. Next, a method is developed to work backwards through the DEA model to provide values that would be the required results from an AHP formulation to give the same result in DEA. The objective of the research is to propose variants of DEA that would possibly improve the results and also integrate subjective data. Through the application of the methods developed in this research, it is believed that the acceptability of the results obtained from DEA analysis can be improved

    Multivariate calibration of CO2 Solubility in iethanolamine (DEA) using Raman Spectroscopy

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    The emission of greenhouse gas which is mainly from carbon dioxide (CO2) have cause phenomena of global warming and climate changes. Thus, this issues has become main focus in worldwide nowadays. CO2 removal process also is an essential step in many industrial processing especially in natural gas processing. Absorption based on alkanolamines like diethanolamine (DEA) have been widely applied in carbon capture plant. CO2 solubility has become an important parameter in the absorption process for proper process control in plant operation. Measurement of CO2 solubility in 10%, 20% and 30% DEA using Raman spectroscopy is the main focus in this research. Raman shift and intensity of different DEA concentration with respect to CO2 loading (mol CO2 / mol amine) are obtained by using Raman spectroscopy. Partial Least Square (PLS) regression approach will be utilized to develop a calibration model that relate the Raman spectroscopy data to CO2 solubility in different concentration of DEA. From the result obtained, 10%, 20% and 30% model have shown great performance and demonstrate good prediction of CO2 solubility. In addition, a combined concentration model and combined modified model is developed to predict CO2 solubility at different DEA concentration. From the study, with the inverse of 900 – 1100 cm-1 are added to predicting matrix, the validation R2 have been increased from 0.9004 to 0.9136. Combination of analytical instrument and multivariate calibration tools will aid the process of online monitoring CO2 solubility in DEA in process plant operation

    Development and Calibration of a System-Integrated Rotorcraft Finite Element Model for Impact Scenarios

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    Two full-scale crash tests of an MD-500 helicopter were conducted in 2009 and 2010 at NASA Langley's Landing and Impact Research Facility in support of NASA s Subsonic Rotary Wing Crashworthiness Project. The first crash test was conducted to evaluate the performance of an externally mounted composite deployable energy absorber (DEA) under combined impact conditions. In the second crash test, the energy absorber was removed to establish baseline loads that are regarded as severe but survivable. The presence of this energy absorbing device reduced the peak impact acceleration levels by a factor of three. Accelerations and kinematic data collected from the crash tests were compared to a system-integrated finite element model of the test article developed in parallel with the test program. In preparation for the full-scale crash test, a series of sub-scale and MD-500 mass simulator tests were conducted to evaluate the impact performances of various components and subsystems, including new crush tubes and the DEA blocks. Parameters defined for the system-integrated finite element model were determined from these tests. Results from 19 accelerometers placed throughout the airframe were compared to finite element model responses. The model developed for the purposes of predicting acceleration responses from the first crash test was inadequate when evaluating more severe conditions seen in the second crash test. A newly developed model calibration approach that includes uncertainty estimation, parameter sensitivity, impact shape orthogonality, and numerical optimization was used to calibrate model results for the full-scale crash test without the DEA. This combination of heuristic and quantitative methods identified modeling deficiencies, evaluated parameter importance, and proposed required model changes. The multidimensional calibration techniques presented here are particularly effective in identifying model adequacy. Acceleration results for the calibrated model were compared to test results and the original model results. There was a noticeable improvement in the pilot and copilot region, a slight improvement in the occupant model response, and an over-stiffening effect in the passenger region. One lesson learned was that this approach should be adopted early on, in combination with the building-block approaches that are customarily used, for model development and pretest predictions. Complete crash simulations with validated finite element models can be used to satisfy crash certification requirements, potentially reducing overall development costs

    Penilaian Teknologi Untuk Menentukan Posisi Industri Pesaing

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    Sumiati Export International Corporation is one of handicraft companies supplied by five small industry of its trainee. Since the company will be privet in a short time, the head office manager wanted one of small industries take over its management. Therefore the company needs to determine one of small industry which is the best. The management intends to make an assessment of technology to five small industries of its trainee internally and externally as the basic of decision making. This research will be held by making an assessment to all of handicraft suppliers by using technometric model approach. In this approach assessment conducted by determining degree of technology component sophistication, valuing state-of-the-art, determining contribution of technology component, making the map of relation between the components, and valuing intensity of contribution components. The questioners spreading to five small industries analyzed by pairwise comparison Analytic Hierarchy Process (AHP) then concluded by the calculation of TCC (Technology Contribution Coefficient). The company made internal assessment by using DEA (data envelopment analysis) model then compare the result of TCC white DEA quantitatively. TCC result showed that the values of the industry in a row are Maharani by 52.23%, Bestari by 52.23%, Priyo by 41.51%, Rizky 32.66%, and Teguh by 31.93%. The greatest contribution for Maharani came from organware while the rest companies came from humanware. In the future, all of small industries expected to develop technology known by technoware. The Result of internal assessment of Sumiati Export International Corporation by DEA model showed that Maharani in the first position and Rizky in the last position. Technometric model with combination of pairwise comparison AHP aids big companies to make technology assessment to small industries

    A modified DEA model to estimate the importance of objectives with an application to agricultural economics

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    This paper demonstrates a connection between Data Envelopment Analysis (DEA) and a non-interactive elicitation method to estimate the weights of objectives for decision-makers in a multiple-attribute approach. This connection gives rise to a modified DEA model that allows us to estimate not only efficiency measures but also preference weights by radially projecting each unit onto a linear combination of the elements of the payoff matrix (which is obtained by standard multicriteria methods). For users of Multiple Attribute Decision Analysis the basic contribution of this paper is a new interpretation in terms of efficiency of the non-interactive methodology employed to estimate weights in a multicriteria approach. We also propose a modified procedure to calculate an efficient payoff matrix and a procedure to estimate weights through a radial projection rather than a distance minimisation. For DEA users, we provide a modified DEA procedure to calculate preference weights and efficiency measures that does not depend on any observations in the dataset. This methodology has been applied to an agricultural case study in Spain.DEPARTMENT OF BUSINESS ADMINISTRATION AND MARKETINGPostprin

    Canonical correlation analysis and DEA for azorean agriculture efficiency

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    In this paper we will document the application of canonical correlation analysis to variable aggregation using the correlations of the original variables with the canonical variates. A case study, about farms in Terceira Island, with a small data set is presented. In this data set of 30 farms we intend to use 17 input variables and 2 output variables to measure DEA efficiency. Without any data reduction procedure several problems known as “curse of dimensionality” are expected. With the data reduction procedures suggested it was possible to conclude quite acceptable and domain consistent conclusions.N/
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