Sains Malaysiana 39(3)(2010): 485–489

 

Setting Targets with Interval Data Envelopment Analysis Models via Wang Method

(Menetapkan Sasaran dengan Model Analisis Pengumpulan Data Selang melalui Kaedah Wang)

 

Najmeh Malekmohammadi*

Institute for Mathematical Research, Universiti Putra Malaysia

43400 Serdang, Selangor D.E. Malaysia

 

Azmi B Jaafar

Faculty of Computer Science and Information Technology, Universiti Putra Malaysia

43400 Serdang, Selangor D.E., Malaysia

 

Mansor Monsi

Institute for Mathematical Research, Universiti Putra Malaysia

43400 Serdang, Selangor D.E., Malaysia

 

Received: 27 February 2009 / Accepted: 2 October 2009

 

ABSTRACT

 

Data envelopment analysis (DEA) is a mathematical programming for evaluating the relative efficiency of decision making units (DMUs). The first DEA model (CCR model) assumed for exact data, later some authors introduced the applications of DEA which the data was imprecise. In imprecise data envelopment analysis (IDEA) the data can be ordinal, interval and fuzzy. Data envelopment analysis also can be used for the future programming of organizations and the response of the different policies, which is related to the target setting and resource allocation. The existing target model that conveys performance based targets in line with the policy making scenarios was defined for exact data. In this paper we improved the model for imprecise data such as fuzzy, ordinal and interval data. To deal with imprecise data we first established an interval DEA model. We used one of the methods to convert fuzzy and ordinal data into the interval data. A numerical experiment is used to illustrate the application to our interval model.

 

Keywords: Imprecise data; interval data envelopment analysis model; target setting

 

ABSTRAK

 

Analisis Pengumpulan Data (DEA) ialah pengaturcaraan bermatematik bagi menilai kecekapan relatif unit pembuat keputusan (DMU). Model DEA pertama (model CCR) mengandaikan data tepat, kemudian beberapa pengarang memperkenalkan penggunaan DEA dengan data tepat. Dalam Analisis Pengumpulan Data tak tepat (IDEA), data boleh dalam bentuk ordinal, selang dan kabur. Analisis pengumpulan data juga boleh digunakan bagi perancangan masa depan sesebuah organisasi dan sebagai maklum balas bagi pelbagai polisi, yang berkait rapat dengan penentuan sasaran dan pengagihan sumber. Model sasaran tersedia yang mengeluarkan prestasi berdasarkan sasaran selari dengan situasi membuat polisi yang ditakrifkan ke atas data tepat. Dalam kertas ini, penambahbaikan model dilaksanakan bagi data taktepat seperti data kabur, ordinal dan data selang. Bagi mengendalikan data taktepat ini, pertamanya dibina sebuah model Analisis Pengumpulan Data Selang. Kami menggunakan salah satu kaedah untuk menukarkan data kabur dan ordinal data kepada data selang. Satu eksperimen berangka dijalankan untuk menunjukkan penggunaannya terhadap model data selang yang dicadangkan kami.

 

Kata kunci: Data tak tepat; Model Analisis Pengumpulan Data Selang; penentuan sasaran

 

REFERENCES

 

Athanassopoulos, A.D. 1995. Goal programming and Data Envelopment Analysis (GoDEA) models for multi-level multi-unit organizations: An application to Greek local authorities. European Journal of Operational Research 87(3): 535-550.

Athanassopoulos, A.D. 1996 Assessing the comparative spatial disadvantage of European using non-radial data envelopment analysis models. European Journal of Operational Research 94: 439-452.

Athanassopoulos, A.D. 1998. A network representation of decentralized target-based resource management of public services. Management Science 44(2): 173-187.

Athanassopoulos, A.D., Lambroukos, N. & Seiford, L.M. 1999. Data envelopment scenario analysis for setting targets to electricity generating plants. European Journal of Operational Research 115: 413-428.

Charnes, A., Cooper, W.W. & Rhodes, E. 1978. Measuring the efficiency of decision making units. European Journal of Operational Research 2(6): 429-444.

Cooper, W.W., Park, K.S. & Yu, G. 1999. IDEA and ARIDEA: models for dealing with imprecise data in DEA. Management Science 45: 597-607.

Cooper, W.W., Park, K.S. & Yu, G. 2001. An illustrative application of IDEA to a Korean mobile telecommunication company. Operations Research 49: 807-820.

Despotis, D.K. & Smirlis, Y.G. 2002. Data envelopment analysis with imprecise data. European Journal of Operational Research 140: 24-36.

Golany, B. 1988. An interactive MOLP procedure for the extension of DEA to effectiveness analysis. Journal of the Operational Research Society 39: 725-734.

Lingo. 2004. www.lindo.com. Thanassoulis, E. & Dyson, R. 1992. Estimating preferred targets input-output levels using data envelopment analysis. European Journal of Operational Research 56: 80-97.

Wang, Y.M., Greatbanksa, R. & Yang, J.B. 2005. Interval efficiency assessment using data envelopment analysis. Fuzzy Sets and Systems 153: 347-370.

Zhu, J. 2003. Imprecise data envelopment analysis (IDEA): A review and improvement with an application. European Journal of Operational Research 144: 513-529.

Zhu, J. 2004. Imprecise DEA via standard linear DEA models with a revisit to a Korean mobile telecommunication company, Operations Research 52: 323-329.

 

*Corresponding author; email: n.malekmohammadi@gmail.com

 

 
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