**6. Discussion**

As the weights of criteria is the most important parameter for the decision maker to choose the best alternative from a bunch of alternatives. So, in order to compute the best alternative, different integrated cross entropy based MCDM are implemented. The result obtained from different MCDM techniques is then compared with the existing result [39]. The result thus obtained from VIKOR method matches with the existing literature whereas the result obtained from other methods fail to match. From the **Table 9** and **Figure 12**, it was observed that the 4 out of the 5 Multi-Criteria Decision Making methods except VIKOR gives exactly the same result. Hence, it is validated and it can be conclude that 80% of the time alternative 4 is the best alternative for the given problem. But, result obtained from VIKOR

*Comparison of Cross-Entropy Based MCDM Approach for Selection of Material in Sugar… DOI: http://dx.doi.org/10.5772/intechopen.98242*


**Table 9.**

*Ranking of alternatives by different MCDM methods.*

**Figure 12.**

*Ranking by different MCDM methods.*


#### **Table 10.**

*Spearman's rank correlation coefficient.*

matches with the [39]. Therefore, a need of comparative analysis arose. The different cross entropy based MCDM methods are compared using Spearman's Rank Correlation Coefficient. From the comparative analysis, the value of rs is tabulated in the **Table 10**. The regression coefficient value R<sup>2</sup> is tabulated in **Table 11**. From both the table it was found that the result obtained from the VIKOR method strongly disagrees with the result that obtained from the COPRAS, MOORA, TOPSIS and modified TOPSIS. Whereas the result obtained from COPRAS, MOORA, TOPSIS and modified TOPSIS are a perfect match. The reason behind this is that ranking of alternatives totally based on the values of the criteria of the alternatives. If the values of the criteria are changed then there is huge probability of the change in rank of the alternatives.
