A hybrid method using experiment design and grey relational analysis for multiple criteria decision making problems

2013 ◽  
Vol 53 ◽  
pp. 100-107 ◽  
Author(s):  
Peng Wang ◽  
Peng Meng ◽  
Ji-Ying Zhai ◽  
Zhou-Quan Zhu
2010 ◽  
Vol 34-35 ◽  
pp. 1931-1935 ◽  
Author(s):  
Qi Bing Wang ◽  
An Hua Peng

Multiple criteria decision making(MCDM) is widely used in selection from a set of available alternatives with multiple criteria, approaches to which includes fuzzy comprehensive evaluation(FCE), grey relational analysis(GRA), and technique for order preference by similarity to ideal solution(TOPSIS), and so on. First analyzes the limitations of various methods: only considering the overall effect of attribute indicators in the method of FCE, only considering the shape similarity of data curve between comparative scheme and ideal solution in GRA and only considering position approximation in TOPSIS. Second proposes a new method of comprehensive evaluation which takes into account both shape similarity and position approximation. The validity of this method has been further proved by an example of suppliers selection.


2013 ◽  
Vol 444-445 ◽  
pp. 666-670
Author(s):  
Yi Zhang

For the multi-attribute decision making with time series, based on the comprehensive consideration of various indicators of quality and growth degree, with grey relational analysis on less data, uncertain information can be integrated comparison, so we put forward a new decision method considering the decision maker subjective views, and provide a scientific and rational decision-making method. By the example, that method is viable.


Author(s):  
Sami Özcan ◽  
Ali Kemal Çelik

<div data-canvas-width="540.0693333333334">The paper aims to compare the results of the selection/choice of cream separators by using multi-criteria decision-making methods in an integrated manner for an enterprise with a dairy processing capacity of 80 to 100 tons per day operating in the Turkish food sector. A total of 7 alternative products and 7 criteria for milk processing were determined. Criterion weights were calculated using entropy method and then integrated into TOPSIS (Technique for Order Preference by Similarity to Ideal Solutions), GRA (Grey Relational Analysis) and COPRAS (Complex Proportional Assessment) methods. Sensitivity analyses were carried out on the results obtained from the three methods to check for their reliability. At the end of the study, similar alternative and appropriate results were found from the TOPSIS and COPRAS methods. However, different alternative but appropriate or suitable results were obtained from the GRA method. Sensitivity analysis of the three methods showed that all the methods used were valid. In the review of available and related literature, very few studies on machine selection in the dairy and food sector in general were found. For this reason, it is thought that the study will contribute to the decision-making process of companies in the dairy sector in their choice of machinery selections. As far as is known, this paper is the first attempt in extant literature to compare in an integrated manner the results of TOPSIS, COPRAS and GRA methods considered in the study.</div>


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