• Title, Summary, Keyword: Data Envelopment Analysis(DEA)

Search Result 538, Processing Time 0.045 seconds

DCBA-DEA: A Monte Carlo Simulation Optimization Approach for Predicting an Accurate Technical Efficiency in Stochastic Environment

  • Qiang, Deng;Peng, Wong Wai
    • Industrial Engineering and Management Systems
    • /
    • v.13 no.2
    • /
    • pp.210-220
    • /
    • 2014
  • This article describes a 2-in-1 methodology utilizing simulation optimization technique and Data Envelopment Analysis in measuring an accurate efficiency score. Given the high level of stochastic data in real environment, a novel methodology known as Data Collection Budget Allocation-Data Envelopment Analysis (DCBA-DEA) is developed. An example of the method application is shown in banking institutions. In addition to the novel approach presented, this article provides a new insight to the application domain of efficiency measurement as well as the way one conducts efficiency study.

An Exploration on the Use of Data Envelopment Analysis for Product Line Selection

  • Lin, Chun-Yu;Okudan, Gul E.
    • Industrial Engineering and Management Systems
    • /
    • v.8 no.1
    • /
    • pp.47-53
    • /
    • 2009
  • We define product line (or mix) selection problem as selecting a subset of potential product variants that can simultaneously minimize product proliferation and maintain market coverage. Selecting the most efficient product mix is a complex problem, which requires analyses of multiple criteria. This paper proposes a method based on Data Envelopment Analysis (DEA) for product line selection. Data Envelopment Analysis (DEA) is a linear programming based technique commonly used for measuring the relative performance of a group of decision making units with multiple inputs and outputs. Although DEA has been proved to be an effective evaluation tool in many fields, it has not been applied to solve the product line selection problem. In this study, we construct a five-step method that systematically adopts DEA to solve a product line selection problem. We then apply the proposed method to an existing line of staplers to provide quantitative evidence for managers to generate desirable decisions to maximize the company profits while also fulfilling market demands.

Technical efficiency of the coastal composite fishery in Korea: a comparison of data envelopment analysis and stochastic frontier analysis

  • Kim, Do-Hoon;Seo, Ju-Nam;Lee, Sang-Go
    • The Journal of Fisheries Business Administration
    • /
    • v.41 no.3
    • /
    • pp.45-58
    • /
    • 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.

Data Envelopment Analysis with Imprecise Data Based on Robust Optimization (부정확한 데이터를 가지는 자료포락분석을 위한 로버스트 최적화 모형의 적용)

  • Lim, Sungmook
    • Journal of the Society of Korea Industrial and Systems Engineering
    • /
    • v.38 no.4
    • /
    • pp.117-131
    • /
    • 2015
  • Conventional data envelopment analysis (DEA) models require that inputs and outputs are given as crisp values. Very often, however, some of inputs and outputs are given as imprecise data where they are only known to lie within bounded intervals. While a typical approach to addressing this situation for optimization models such as DEA is to conduct sensitivity analysis, it provides only a limited ex-post measure against the data imprecision. Robust optimization provides a more effective ex-ante measure where the data imprecision is directly incorporated into the model. This study aims to apply robust optimization approach to DEA models with imprecise data. Based upon a recently developed robust optimization framework which allows a flexible adjustment of the level of conservatism, we propose two robust optimization DEA model formulations with imprecise data; multiplier and envelopment models. We demonstrate that the two models consider different risks regarding imprecise efficiency scores, and that the existing DEA models with imprecise data are special cases of the proposed models. We show that the robust optimization for the multiplier DEA model considers the risk that estimated efficiency scores exceed true values, while the one for the envelopment DEA model deals with the risk that estimated efficiency scores fall short of true values. We also show that efficiency scores stratified in terms of probabilistic bounds of constraint violations can be obtained from the proposed models. We finally illustrate the proposed approach using a sample data set and show how the results can be used for ranking DMUs.

The Efficiency and Business Strategy of Contract-Foodservice Operations using Data Envelopment Analysis (DEA기법을 도입한 위탁 급식 점포의 효율성과 사업 전략에 관한 연구)

  • Choi, Kyu-Wan;Park, Ju-Yeon
    • Journal of the East Asian Society of Dietary Life
    • /
    • v.17 no.5
    • /
    • pp.727-737
    • /
    • 2007
  • The aims of this study was to suggest a new efficiency measurement indicator for evaluating the management efficiency of decision making units(DMUs) in the contract foodservice industry. The data envelopment analysis(DEA) model which considers multiple inputs and outputs and looking for benchmarks, was used to compare the productivity of DMUs. We considered sales, profits, and customer satisfaction as output variables and it adopted food cost, labor cost and administrative expense as input variables. The results of applying DEA revealed relatively efficient types of business and service types. The efficiency of school units was highest and the mired service type was the most efficient one. In this study the CCR model efficiency was analysed with profit and the customer satisfaction index by the matrix method. DEA efficiency was correlated with profit but there was no correlation between DEA efficiency and the customer satisfaction index.

  • PDF

Imprecise DEA Efficiency Assessments : Characterizations and Methods

  • Park, Kyung-Sam
    • Management Science and Financial Engineering
    • /
    • v.14 no.2
    • /
    • pp.67-87
    • /
    • 2008
  • Data envelopment analysis (DEA) has proven to be a useful tool for assessing efficiency or productivity of organizations which is of vital practical importance in managerial decision making. While DEA assumes exact input and output data, the development of imprecise DEA (IDEA) broadens the scope of applications to efficiency evaluations involving imprecise information which implies various forms of ordinal and bounded data possibly or often occurring in practice. The primary purpose of this article is to characterize the variable efficiency in IDEA. Since DEA describes a pair of primal and dual models, also called envelopment and multiplier models, we can basically consider two IDEA models: One incorporates imprecise data into envelopment model and the other includes the same imprecise data in multiplier model. The issues of rising importance are thus the relationships between the two models and how to solve them. The groundwork we will make includes a duality study which makes it possible to characterize the efficiency solutions from the two models. This also relates to why we take into account the variable efficiency and its bounds in IDEA that some of the published IDEA studies have made. We also present computational aspects of the efficiency bounds and how to interpret the efficiency solutions.

Productive Efficiency of the Coastal Fishing Business : A Comparison of Data Envelopment Analysis and Stochastic Frontier Analysis (연안어업경영의 생산효율성 분석 : DEA와 SFA 기법 비교를 중심으로)

  • Choi, Jong-Yeol;Kim, Ki-Seog;Kim, Do-Hoon
    • Journal of the Korean Operations Research and Management Science Society
    • /
    • v.35 no.3
    • /
    • pp.59-68
    • /
    • 2010
  • Improving productive efficiency is important for strengthening a competitiveness of coastal fisheries. This paper examines the productive efficiency of a sample of coastal gillnet fishing business units by estimating a stochastic frontier analysis (SFA) and a data envelopment analysis (DEA) approaches and compares those estimates obtained from two approaches. The estimated mean productive efficiency by SFA is 77.6% and the mean productive efficiencies obtained for the VRS and CRS DEA are 75.9% and 45.7%, respectively. The joint use of SFA and DEA for estimating efficiency is also discussed.

The Analysis Method of Integrated Logistic System using Evolution Strategies and Data Envelopment Analysis (진화전략과 DEA를 이용한 통합 물류 시스템 분석 방법)

  • Um In-Sup;Lee Hong-Chul;Kang Jeong-Yun
    • Journal of the Korea Society for Simulation
    • /
    • v.13 no.4
    • /
    • pp.17-29
    • /
    • 2004
  • The focus of this study is to represent a methodology of analysis for integrated logistic system by means of the Evolution Strategies and Data Envelopment Analysis(DEA). The integrated logistic system is composed of AS/RS (Automated Storages and Retrieval System), AGVs(Automated Guided Vehicle System) and Conveyor System. We design the simulation alternatives with choosing the qualitative critical factors for the each subsystem. Evolution Strategies is used to optimize the quantitative critical factors and responses of each alternative. DEA is applied to measure the efficiency of the alternatives in order to select the optimal operation efficiency scheme. The method of analysis which combines Evolution Strategies with DEA can be used to analyze the qualitative and quantitative critical factors in the integrated logistic systems.

  • PDF

A Comparative Study of Technological Forecasting Methods with the Case of Main Battle Tank by Ranking Efficient Units in DEA (DEA기반 순위선정 절차를 활용한 주력전차의 기술예측방법 비교연구)

  • Kim, Jae-Oh;Kim, Jae-Hee;Kim, Sheung-Kown
    • Journal of the military operations research society of Korea
    • /
    • v.33 no.2
    • /
    • pp.61-73
    • /
    • 2007
  • We examined technological forecasting of extended TFDEA(Technological Forecasting with Data Envelopment Analysis) and thereby apply the extended method to the technological forecasting problem of main battle tank. The TFDEA has the possibility of using comparatively inefficient DMUs(Decision Making Units) because it is based on DEA(Data Envelopment Analysis), which usually leads to multiple efficient DMUs. Therefore, TFDEA may result in incorrect technological forecasting. Instead of using the simple DEA, we incorporated the concept of Super-efficiency, Cross-efficiency, and CCCA(Constrained Canonical Correlation Analysis) into the TFDEA respectively, and applied each method to the case study of main battle tank using verifiable practical data sets. The comparative analysis shows that the use of CCCA with TFDEA results in very comparable prediction accuracies with respect to MAE(Mean Absolute Error), MSE(Mean Squared Error), and RMSE(Root Mean Squared Error) than using the concept of Super-efficiency and Cross-efficiency.