Choosing a solar panel supplier means balancing product performance, reliable delivery, warranty coverage, and price. This example uses Fuzzy VIKOR to compare four named manufacturers with a five-point linguistic scale.
A procurement team selecting modules for a commercial or utility-scale solar project must decide which supplier offers the strongest overall compromise. The choice can affect generation, project risk, and procurement cost.
Decision Criteria and Alternatives
- Module efficiency (0.35): Higher efficiency can produce more power from limited area.
- Product warranty (0.25): Coverage can reduce long-term ownership risk.
- Delivery reliability (0.20): Dependable supply helps protect the installation schedule.
- Quoted price (0.20, cost criterion): Lower prices improve affordability, so this criterion is negative.
The alternatives are Jinko Solar, Canadian Solar, First Solar, and Trina Solar. The crisp weights sum to 1.00.
Input Data and Linguistic Scale
One expert rated suppliers from 1 (Very Low) to 5 (Very High); the software converts the codes to fuzzy triangular values. Selected entries from the decision matrix:
| Supplier | Module efficiency | Quoted price |
|---|---|---|
| Jinko Solar | 5 — Very High | 3 — Medium |
| Trina Solar | 4 — High | 2 — Low |
Run the Example in Fuzzy VIKOR
The model was entered and calculated in the Fuzzy VIKOR software. See the complete online output, including the decision matrix and compromise check.
Results and Interpretation
Trina Solar has the lowest crisp Q (0.010) and ranks first by S, R, and Q. Jinko Solar ranks second, Canadian Solar third, and First Solar fourth.
| Supplier | S (rank) | R (rank) | Q (rank) |
|---|---|---|---|
| Trina Solar | 0.108 (1) | 0.181 (1) | 0.010 (1) |
| Jinko Solar | 0.112 (2) | 0.194 (2) | 0.020 (2) |
| Canadian Solar | 0.117 (3) | 0.238 (3) | 0.042 (3) |
| First Solar | 0.217 (4) | 0.458 (4) | 0.248 (4) |
The acceptable-advantage condition is not met, while the stability condition is met. Therefore, the software returns a compromise set containing all four suppliers. Trina is the top-ranked candidate in this example, but not a unique VIKOR compromise winner. These ratings are illustrative judgments, not verified supplier quotations or performance claims.
Download this run as an Excel workbook or a Word report.
Practical Takeaways
Define criteria in measurable terms and confirm which are costs before rating alternatives. Agree on weights with stakeholders, then test whether the leading supplier changes when weights or judgments shift. Use any compromise set as a shortlist for technical, commercial, and due-diligence review.
Frequently Asked Questions
What does Fuzzy VIKOR do in supplier selection?
It compares alternatives against weighted criteria with fuzzy linguistic ratings and checks whether the result is a compromise solution.
Why is quoted price a negative criterion?
A higher quoted price is less desirable, so the model treats price as a cost to minimize.
Which supplier ranks first here?
Trina Solar has the lowest Q (0.010) and ranks first in S, R, and Q. The compromise set still includes all four suppliers because acceptable advantage is not satisfied.
Can I view or download the calculations?
Yes. Open the online result or download the Excel or Word file.
Explore the Method and Software
Try the Fuzzy VIKOR software with your own data, and read the Fuzzy VIKOR method guide for the ranking logic.