Illustrative example: a representative scenario, not a customer story
PhD Thesis: Material Selection
Doctoral research comparing 5 ranking methods and 3 weight methods for composite material selection. Multi-method agreement analysis validates robustness.
The decision problem
A doctoral study selects a composite material, and the contribution is the comparison itself rather than a single winner. A referee asks the same two questions every time: would another weighting method have changed the order, and would another ranking method have changed it. So one matrix is run through several methods and the study reports how far the resulting orders agree.
What the decision matrix looks like
The typical shape of a study like this. Your own matrix can be larger or smaller; nothing here is fixed.
9
Alternatives
5
Criteria
Method choice uncertainty
Uncertainty type
| # | Criterion |
|---|---|
| C1 | Tensile strength |
| C2 | Density |
| C3 | Cost |
| C4 | Corrosion resistance |
| C5 | Recyclability |
Which method, and why
Entropy and CRITIC produce objective weights from different signals, Entropy from the spread within a criterion and CRITIC from the correlation between criteria, so the weighting question is answered with evidence rather than preference. VIKOR, CODAS and WASPAS then rank the same matrix from a compromise, a distance and an aggregation standpoint. The agreement between those orders is the robustness claim the thesis defends.
What you get out
Ranking and scores
Every alternative with its score, its rank and the intermediate matrices that produced them.
Weight sensitivity
One criterion weight moves at a time, so you see exactly where the leader changes.
Method agreement
When more than one ranking method is run, the orders are compared with Spearman rho and Kendall W.
Report and citation
PDF, DOCX and XLSX output carrying the seminal source of every method used.
Run this flow on your own data
Load the matrix, choose the weighting and ranking methods, read the sensitivity.