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Information Journal Paper

Title

GENETIC ALGORITHM TO MEASURE THE EFFICIENCY OF LARGE-SCALE PROBLEMS IN DATA ENVELOPMENT ANALYSIS

Pages

  109-124

Abstract

DATA ENVELOPMENT ANALYSIS (DEA) is one of the successful evaluation methods for measuring the relative EFFICIENCY of Decision Making Units (DMUs) that utilizes techniques of mathematical programming. In DEA models, for measuring the relative EFFICIENCY of DMUs, for a large dataset with many inputs/outputs would need to have a long time with a huge computer. This paper developed the GENETIC ALGORITHM (GA) for DEA. GA requirements for computer memory and CPU time are far less than that needed by conventional DEA methods and can therefore be a useful tool in measuring the EFFICIENCY of large datasets. Since the operators have important roles on the fitness of the algorithms, all the operators and parameters are calibrated by means of the Taguchi experimental design in order to improve their performances.

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    Cite

    APA: Copy

    MAHMOODIRAD, A., SANEI, M., & MOLLA ALIZADEH ZAVARDEHI, S.. (2015). GENETIC ALGORITHM TO MEASURE THE EFFICIENCY OF LARGE-SCALE PROBLEMS IN DATA ENVELOPMENT ANALYSIS. JOURNAL OF OPERATIONAL RESEARCH AND ITS APPLICATIONS (JOURNAL OF APPLIED MATHEMATICS), 12(2 (45)), 109-124. SID. https://sid.ir/paper/164656/en

    Vancouver: Copy

    MAHMOODIRAD A., SANEI M., MOLLA ALIZADEH ZAVARDEHI S.. GENETIC ALGORITHM TO MEASURE THE EFFICIENCY OF LARGE-SCALE PROBLEMS IN DATA ENVELOPMENT ANALYSIS. JOURNAL OF OPERATIONAL RESEARCH AND ITS APPLICATIONS (JOURNAL OF APPLIED MATHEMATICS)[Internet]. 2015;12(2 (45)):109-124. Available from: https://sid.ir/paper/164656/en

    IEEE: Copy

    A. MAHMOODIRAD, M. SANEI, and S. MOLLA ALIZADEH ZAVARDEHI, “GENETIC ALGORITHM TO MEASURE THE EFFICIENCY OF LARGE-SCALE PROBLEMS IN DATA ENVELOPMENT ANALYSIS,” JOURNAL OF OPERATIONAL RESEARCH AND ITS APPLICATIONS (JOURNAL OF APPLIED MATHEMATICS), vol. 12, no. 2 (45), pp. 109–124, 2015, [Online]. Available: https://sid.ir/paper/164656/en

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