Base-criterion on multi-criteria decision-making method and its applications

ABSTRACT

In this paper, Base-criterion method (BCM) is proposed to solve multi-criteria decision-making problems. According to BCM, instead of executing a pairwise comparisons between all criteria or executing a pairwise comparisons between each of the best and worst criteria to other criteria, one of the criteria is chosen by the decision-maker as a base-criterion (e.g. preferential, selective) and then pairwise comparisons between base-criterion and other criteria are obtained. Then, a max-min problem is formulated and solved to determine the weight of the criteria. In this way, the pairwise comparisons to obtain weights of the criteria are fully consistent. In other ability of BCM, we find the lost pairwise comparisons by using the BCM framework so that the pairwise comparisons matrix remains consistent. To illustrate the reliability of the proposed method and evaluate its performance to determine the weights, we have used two numerical examples. The outcomes of numerical examples indicate that the BCM has high accuracy and better consistency ratio than the other multi-criteria decision-making(MCDM) methods. The cause of high consistency ratio in the BCM is the dependency of pairwise comparisons between criteria. Moreover, we have used two other numerical examples to illustrate the function of the BCM in order to find out the missing comparisons in incomplete pairwise comparison matrix. We have shown the BCM framework able to find lost comparisons in the worst terms of the incomplete pairwise comparison matrix. The outcomes of the proposed article show that BCM performance is significantly better than AHP and BWM methods with respect to the consistency ratio, and it requires fewer comparison data and has the ability to calculate missing pairwise comparisons.

KEYWORDS:

• Multi-criteria decision making
• multi-attribute decision making
• pairwise comparison
• incomplete data
• consistency ratio

Notes

1. Technique for Order of Preference by Similarity to Ideal Solution.

2. VlseKriterijumskaOptimizacija I KompromisnoResenje.

3. Complex Proportional Assessment.

4. Elimination Et ChoixTraduisantlaREaite.

5. Preference Ranking Organization METHod for Enrichment Evaluations.

6. Analytic Hierarchy Process.

7. Analytic network process.

8. Step-wise Weight Assessment Ratio Analysis.

9. Best-Worst Method.