A fuzzy multiple objective programming to dea with imprecise data

被引：10

作者：

Yu, JR ^{[1
]}

Tzeng, YC

Tzeng, GH

Yu, TY

Sheu, HJ

机构：

[1] Natl Chi Nan Univ, Dept Informat Management, Puli Nantou 545, Taiwan

[2] Inotera Memories Inc, Taoyuan, Taiwan

[3] Natl Chiao Tung Univ, Inst Technol Management, Hsinchu 30050, Taiwan

[4] Natl Chiao Tung Univ, Dept Management Sci, Hsinchu 30050, Taiwan

来源：

INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS | 2004年 / 12卷 / 05期

关键词：

data envelopment analysis; fuzzy multiple objective programming; imprecise data;

D O I：

10.1142/S0218488504003090

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A fuzzy multiple objective programming approach to data envelopment analysis (DEA) of imprecise data is proposed in this paper. The problems involving a mixture of imprecise and exact data for all decision making units (DMUs) could be resolved and the discriminating power of imprecise DEA (IDEA) is enhanced. Although Cooper et al. have developed IDEA to overcome the issues of imprecise data, the discriminating power is not satisfactory since too many efficient DMUs are derived. Chiang and Tzeng's approach using fuzzy multiple objective programming techniques is adopted to enhance the discriminating power of IDEA. The same data set of Cooper et al. is employed to illustrate the merit of our approach.

引用

页码：591 / 600

页数：10

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