Evaluating decision-making units under uncertainty using fuzzy multi-objective nonlinear programming
This paper proposes a new method to evaluate decision-making units (DMUs) under uncertainty using fuzzy data envelopment analysis (DEA).In the proposed multi-objective nonlinear programming methodology, both the objective functions and the constraints are considered fuzzy.This model is comprehensive...
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| 主要な著者: | , , , , , , |
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| フォーマット: | 論文 |
| 出版事項: |
Taylor & Francis Group
2017
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| 主題: | |
| オンライン･アクセス: | http://repo.uum.edu.my/21583/ http://doi.org/10.1080/03155986.2016.1240944 |
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| 要約: | This paper proposes a new method to evaluate decision-making units (DMUs) under uncertainty using fuzzy data envelopment analysis (DEA).In the proposed multi-objective nonlinear programming methodology, both the objective functions and the constraints are considered fuzzy.This model is comprehensive in dealing with uncertainty, in the sense that coefficients of the decision variables in the objective functions and in the constraints, as well as the DMUs under assessment, are assumed to be fuzzy numbers with triangular membership functions. A comparison between the current fuzzy DEA models and the proposed method is illustrated by a numerical example. |
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