Hesitant Fuzzy SWARA-Complex Proportional Assessment Approach for Sustainable Supplier Selection (HF-SWARA-COPRAS)
Abstract
:1. Introduction
- ▪
- A novel HF-SWARA-COPRAS method is introduced.
- ▪
- The criteria weights are evaluated by the SWARA method.
- ▪
- To illustrate the feasibility and usefulness of the HF-SWARA-COPRAS method, an empirical case study of SSS problem is discussed under HFSs environment.
- ▪
- Sensitivity analysis and comparative study are discussed to confirm the stability and validity of the developed methodology.
2. Literature Review
2.1. Hesitant Fuzzy Sets
2.2. Step-Wise Weight Assessment Ratio Analysis (SWARA)
2.3. Complex Proportional Assessment (COPRAS) Approach
2.4. Sustainable Supplier Selection (SSS)
3. Proposed Methodology
3.1. Prerequisites
3.2. Hesitant Fuzzy SWARA-COPRAS Method
4. An Empirical Study: Sustainable Supplier Selection (SSS)
4.1. Sensitivity Analysis
4.2. Comparison with Existing Methods
- The HFS can reflect the DE’s hesitancy more objectively than other classical extensions of FS. Therefore, the use of the developed HF-SWARA-COPRAS approach gives a more flexible way to express the uncertainty in the selection of SS.
- The SWARA method is employed to evaluate the criteria weights in the evaluation of the SSS process, which makes the introduced HF-SWARA-COPRAS method more reliable, efficient and sensible tool.
- The proposed HF-SWARA-COPRAS can process the information in a more useful and suitable way and from different perspectives, such as benefit-type and cost-type criteria.
4.3. Discussion and Implications
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Dimension | Criteria | Meaning | Type |
---|---|---|---|
Economic [7,13,91,92] | Quality (F1) | The overall quality of products. | Benefit |
Cost (F2) | Price and the share of transaction costs per unit product. | Cost | |
Production Capacity (F3) | Single-shift production per day. | Benefit | |
Environmental [7,13,88,93] | Eco-design (F4) | Refers the design of products for reduced consumption of material/energy, reuse and recycling. | Benefit |
Sustainable Materials (F5) | The level of sustainable materials utilized in manufacturing and packaging per product. | Benefit | |
Pollution (F6) | Refers the average amount of air pollutants, wastes and hazardous materials released per day. | Cost | |
Industry Reputation (F7) | The degree of social recognition of corporate behavior. | Benefit | |
Social [13,88,92,94] | Health and safety (F8) | Including Occupational Safety and Health (OHSAS) 18001, conditions and incidents. | Benefit |
LVs | HFNs | DEs Risk Preference | ||
---|---|---|---|---|
Pessimist | Moderate | Optimist | ||
Very High (VH) | [0.8, 0.9] | 0.80 | 0.85 | 0.90 |
High (H) | [0.70, 0.8] | 0.70 | 0.75 | 0.80 |
Medium (M) | [0.55, 0.70] | 0.55 | 0.625 | 0.70 |
Low (L) | [0.40, 0.55] | 0.40 | 0.475 | 0.55 |
Very Low (VL) | [0.25, 0.40] | 0.25 | 0.325 | 0.40 |
LVs | HFNs | DEs Risk Preference | ||
---|---|---|---|---|
Pessimist | Moderate | Optimist | ||
Extremely Preferable (EP) | [0.9, 1.0] | 0.9 | 0.95 | 1.00 |
Strong Preferable (SP) | [0.75, 0.9] | 0.75 | 0.825 | 0.9 |
Preferable (P) | [0.6, 0.75] | 0.6 | 0.675 | 0.75 |
Moderate (M) | [0.45, 0.6] | 0.45 | 0.525 | 0.6 |
Undesirable (U) | [0.35, 0.45] | 0.35 | 0.4 | 0.45 |
Strong Undesirable (SU) | [0.2, 0.35] | 0.2 | 0.275 | 0.35 |
Extremely Undesirable (EU) | [0.0, 0.15] | 0.00 | 0.075 | 0.15 |
G1 | G2 | G3 | G4 | G5 | |
---|---|---|---|---|---|
F1 | {0.2, 0.3, 0.7} | {0.3, 0.4, 0.8} | {0.4, 0.6, 0.7} | {0.5, 0.7, 0.9} | {0.1, 0.4, 0.5} |
F2 | {0.5, 0.6,0.7} | {0.5, 0.7,0.8} | {0.4, 0.5, 0.7} | {0.5,0.8, 0.9} | {0.5, 0.7, 0.9} |
F3 | {0.4,0.5, 0.7} | {0.7, 0.8,0.9} | {0.5, 0.6,0.9} | {0.2,0.6, 0.7} | {0.3, 0.5, 0.8} |
F4 | {0.4, 0.6, 0.8} | {0.4, 0.8, 0.9} | {0.1, 0.2, 0.4} | {0.3, 0.6, 0.8} | {0.2, 0.5, 0.8} |
F5 | {0.3, 0.4, 0.6} | {0.4, 0.7, 0.9} | {0.3, 0.6, 0.7} | {0.4, 0.7, 0.8} | {0.2, 0.5, 0.6} |
F6 | {0.3, 0.5, 0.7} | {0.1,0.5, 0.8} | {0.4, 0.6, 0.7} | {0.2, 0.5, 0.9} | {0.2, 0.7, 0.9} |
F7 | {0.3, 0.5, 0.8} | {0.6, 0.7, 0.8} | {0.3, 0.5, 0.6} | {0.2, 0.4, 0.8} | {0.2, 0.3, 0.7} |
F8 | {0.1, 0.3,0.4} | {0.2, 0.5,0.8} | {0.6, 0.7,0.9} | {0.3, 0.4, 0.9} | {0.3, 0.6, 0.8} |
G1 | G2 | G3 | G4 | G5 | |
---|---|---|---|---|---|
F1 | 0.435 | 0.548 | 0.577 | 0.744 | 0.346 |
F2 | 0.603 | 0.682 | 0.544 | 0.777 | 0.744 |
F3 | 0.544 | 0.813 | 0.717 | 0.533 | 0.575 |
F4 | 0.627 | 0.762 | 0.237 | 0.607 | 0.555 |
F5 | 0.440 | 0.727 | 0.554 | 0.662 | 0.449 |
F6 | 0.519 | 0.537 | 0.577 | 0.641 | 0.699 |
F7 | 0.575 | 0.706 | 0.474 | 0.527 | 0.435 |
F8 | 0.271 | 0.555 | 0.762 | 0.635 | 0.607 |
Criteria | LVs is given by DEs | HFNs Given by DEs | |||||
---|---|---|---|---|---|---|---|
B1 | B2 | B3 | B1 | B2 | B3 | ||
F1 | SU | P | P | 0.2 | 0.675 | 0.75 | 0.589 |
F2 | M | P | P | 0.45 | 0.675 | 0.75 | 0.639 |
F3 | U | M | M | 0.35 | 0.525 | 0.6 | 0.496 |
F4 | M | M | P | 0.45 | 0.525 | 0.75 | 0.588 |
F5 | M | M | M | 0.45 | 0.525 | 0.6 | 0.524 |
F6 | P | P | P | 0.6 | 0.675 | 0.75 | 0.676 |
F7 | U | P | EP | 0.35 | 0.675 | 0.9 | 0.712 |
F8 | SP | M | SP | 0.75 | 0.525 | 0.9 | 0.763 |
Criteria | Crisp Values | Comparative Significance of Criteria Value | Coefficient | Recalculated Weight | Criteria Weight |
---|---|---|---|---|---|
F8 | 0.763 | - | 1.000 | 1.000 | 0.1429 |
F7 | 0.712 | 0.051 | 1.051 | 0.951 | 0.1359 |
F6 | 0.676 | 0.036 | 1.036 | 0.918 | 0.1312 |
F2 | 0.639 | 0.037 | 1.037 | 0.885 | 0.1264 |
F1 | 0.589 | 0.050 | 1.050 | 0.843 | 0.1204 |
F4 | 0.588 | 0.001 | 1.001 | 0.842 | 0.1203 |
F5 | 0.524 | 0.064 | 1.064 | 0.791 | 0.1130 |
F3 | 0.496 | 0.028 | 1.028 | 0.769 | 0.1099 |
SSS Option | Ranking | ||||
---|---|---|---|---|---|
G1 | 0.394 | 0.192 | 0.333 | 80.73% | 4 |
G2 | 0.586 | 0.218 | 0.412 | 100.00% | 1 |
G3 | 0.483 | 0.191 | 0.378 | 91.58% | 2 |
G4 | 0.517 | 0.277 | 0.353 | 85.53% | 3 |
G5 | 0.406 | 0.281 | 0.296 | 71.76% | 5 |
G1 | G2 | G3 | G4 | G5 | |
---|---|---|---|---|---|
0.0 | 0.272 | 0.239 | 0.273 | 0.188 | 0.186 |
0.1 | 0.284 | 0.274 | 0.294 | 0.221 | 0.208 |
0.2 | 0.296 | 0.308 | 0.315 | 0.254 | 0.230 |
0.3 | 0.309 | 0.343 | 0.336 | 0.287 | 0.252 |
0.4 | 0.321 | 0.378 | 0.357 | 0.320 | 0.274 |
0.5 | 0.333 | 0.412 | 0.378 | 0.353 | 0.296 |
0.6 | 0.345 | 0.447 | 0.399 | 0.386 | 0.318 |
0.7 | 0.357 | 0.482 | 0.420 | 0.418 | 0.340 |
0.8 | 0.369 | 0.516 | 0.441 | 0.451 | 0.362 |
0.9 | 0.382 | 0.551 | 0.462 | 0.484 | 0.384 |
1.0 | 0.394 | 0.586 | 0.483 | 0.517 | 0.406 |
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Rani, P.; Mishra, A.R.; Krishankumar, R.; Mardani, A.; Cavallaro, F.; Soundarapandian Ravichandran, K.; Balasubramanian, K. Hesitant Fuzzy SWARA-Complex Proportional Assessment Approach for Sustainable Supplier Selection (HF-SWARA-COPRAS). Symmetry 2020, 12, 1152. https://doi.org/10.3390/sym12071152
Rani P, Mishra AR, Krishankumar R, Mardani A, Cavallaro F, Soundarapandian Ravichandran K, Balasubramanian K. Hesitant Fuzzy SWARA-Complex Proportional Assessment Approach for Sustainable Supplier Selection (HF-SWARA-COPRAS). Symmetry. 2020; 12(7):1152. https://doi.org/10.3390/sym12071152
Chicago/Turabian StyleRani, Pratibha, Arunodaya Raj Mishra, Raghunathan Krishankumar, Abbas Mardani, Fausto Cavallaro, Kattur Soundarapandian Ravichandran, and Karthikeyan Balasubramanian. 2020. "Hesitant Fuzzy SWARA-Complex Proportional Assessment Approach for Sustainable Supplier Selection (HF-SWARA-COPRAS)" Symmetry 12, no. 7: 1152. https://doi.org/10.3390/sym12071152