2019-05-25T19:19:32Z
http://ijo.iaurasht.ac.ir/?_action=export&rf=summon&issue=110643
Iranian Journal of Optimization
IJO
2588-5723
2588-5723
2011
03
1
COMMON WEIGHTS DETERMINATION IN DATA ENVELOPMENT ANALYSIS
Alireza
Amirteimoori
Sohrab
Kordrostami
<span>In models of data envelopment analysis (</span><span>DEA</span><span>), an optimal set of weights is generally assumed to represent the assessed decision making unit (</span><span>DMU</span><span>) in the best light in comparison to all the other </span><span>DMU</span><span>s, and so there is an optimal set of weights corresponding to each </span><span>DMU</span><span>. The present paper, proposes a three stage method to determine one common set of weights for decision making units. Then, we use these weights to rank efficient units. We demonstrate the approach by applying it to rank gas companies. </span>
Data envelopment analysis
Common Set of Weights
Ranking
2009
10
01
199
210
http://ijo.iaurasht.ac.ir/article_513956_0b5f2e6da337d2a12c9a1d9ec414a9d9.pdf
Iranian Journal of Optimization
IJO
2588-5723
2588-5723
2011
03
1
Using lexicographic parametric programming for identifying efficient hyperpalnes in DEA
Farhad
Hosseinzadeh Lotfi
F.
Rezaie Balf
A.
Taghavi
<span>This paper investigates a procedure for identifying all efficient hyperplanes of production possibility set (PPS). This procedure is based on a method which recommended by Pekka J. Korhonen[8]. He offered using of lexicographic parametric programming method for recognizing all efficient units in data envelopment analysis (DEA). In this paper we can find efficient hyperplanes, via using the parameterization of the right hand side vector of the envelopment problem of each efficient unit. </span>
efficiency analysis
Data envelopment analysis
Lexicographic
Parametric programming
Efficient hyperplanes
2009
10
01
211
229
http://ijo.iaurasht.ac.ir/article_513957_fc780b28e445c6b5eabf205c4752922b.pdf
Iranian Journal of Optimization
IJO
2588-5723
2588-5723
2011
03
1
IMPORTANT ISSUES IN MULTIPLE RESPONSE OPTIMIZATION
Mohammad
Taleghani
<span>There have been many p</span><span>r</span><span>oductive met</span><span>hod</span><span>s </span><span>d</span><span>evelope</span><span>d </span><span>so far for o</span><span>p</span><span>t</span><span>imi</span><span>z</span><span>at</span><span>i</span><span>on o</span><span>f </span><span>multipl</span><span>e response su</span><span>r</span><span>face (MRS) pro</span><span>b</span><span>le</span><span>ms</span><span>. T</span><span>hi</span><span>s </span><span>p</span><span>aper ten</span><span>d</span><span>s to rev</span><span>iew the </span><span>m</span><span>o</span><span>s</span><span>t sem</span><span>i</span><span>nal </span><span>appr</span><span>o</span><span>ac</span><span>h</span><span>es in MRS and </span><span>d</span><span>iscuss the </span><span>streng</span><span>th and weakness of e</span><span>ach o</span><span>f </span><span>t</span><span>he a</span><span>pproaches </span><span>t</span><span>hrou</span><span>gh existing aspects in MRS. A n</span><span>u</span><span>merical example is in</span><span>c</span><span>lu</span><span>d</span><span>ed </span><span>to </span><span>compare res</span><span>ults b</span><span>y different methods</span><span>. </span><span>F</span><span>i</span><span>nall</span><span>y </span><span>some of the pr</span><span>o</span><span>minent ar</span><span>e</span><span>as for </span><span>f</span><span>uture r</span><span>e</span><span>search discusse</span><span>d b</span><span>y differen</span><span>t </span><span>researche</span><span>r</span><span>s are presente</span><span>d</span><span>. </span>
Experimental design
Multiple - Response Surface
Response surface methodology
Optimization
2009
10
01
235
247
http://ijo.iaurasht.ac.ir/article_513958_d4b5d33054959b14859296926f7564a4.pdf
Iranian Journal of Optimization
IJO
2588-5723
2588-5723
2011
03
1
THE APPLICATION OF DATA ENVELOPMENT ANALYSIS METHODOLOGY TO IMPROVE THE BENCHMARKING PROCESS IN THE EFQM BUSINESS MODEL (CASE STUDY: AUTOMOTIVE INDUSTRY OF IRAN)
K.
Shahroudi
This paper reports a survey and case study research outcomes on the application of Data Envelopment Analysis (DEA) to the ranking method of European Foundation for Quality Management (EFQM) Business Excellence Model in Iran’s Automotive Industry and improving benchmarking process after assessment. Following the global trend, the Iranian industry leaders have introduced the EFQM practice to their supply chain in order to improve the supply base competitiveness during the last four years. A question which is raises is whether the EFQM model can be combined with a mathematical model such as DEA in order to generate a new ranking method and develop or facilitate the benchmarking process. The developed model of this paper is simple. However, it provides some new and interesting insights. The paper assesses the usefulness and capability of the DEA technique to recognize a new scoring system in order to compare the classical ranking method and the EFQM business model. We used this method to identify meaningful exemplar companies for each criterion of the EFQM model then we designed a road map based on realistic targets in the criterion which have currently been achieved by exemplar companies. The research indicates that the DEA approach is a reliable tool to analyze the latent knowledge of scores generated by conducting self- assessments. The Wilcoxon Rank Sum Test is used to compare two scores and the Test of Hypothesis reveals the meaningful relation between the EFQM and DEA new ranking methods. Finally, we drew a road map based on the benchmarking concept using the research results.
Data envelopment analysis
EFQM Excellence Model
Wilcoxon Rank Sum Test
Benchmarking
Road map
2009
10
01
243
265
http://ijo.iaurasht.ac.ir/article_513959_84c9ae0eb54e5336a7765513cacb1e4f.pdf