SIWEC-R: A rank-sensitive improvement to SIWEC methodology
DOI:
https://doi.org/10.24036/teknomekanik.v8i2.40172Keywords:
MCDM, SIWEC method, R method, SIWEC-R, UTACAbstract
Determining the weights of criteria is a critical step in ranking alternatives characterized by multiple, often conflicting criteria which is a core challenge in Multi-Criteria Decision Making (MCDM). This study introduces the SIWEC-R method, a novel two-stage approach that integrates the SIWEC and R methodology to achieve more accurate and reliable weighting of criteria. Alongside the SIWEC-R method, a new performance metric, the UTAC score, was introduced to capture ranking consistency and strength across various MCDM methods. To ensure a comprehensive evaluation, sensitivity analysis was extended to cover all possible subsets of alternatives, offering an unprecedented level of scrutiny. Comparative assessments across three diverse case studies demonstrated that SIWEC-R consistently outperforms the original SIWEC method, achieving higher Spearman rank correlation coefficients and demonstrating superior robustness under sensitivity analysis. These compelling results firmly establish SIWEC-R as a significant advancement in the field of criteria weighting, delivering enhanced decision-making reliability for complex and uncertain environments.
Downloads
References
Z. Chen, P. Zhong, M. Liu, Q. Ma, and G. Si, “An integrated expert weight determination method for design concept evaluation,” Sci Rep, vol. 12, no. 1, p. 6358, Apr. 2022, https://doi.org/10.1038/s41598-022-10333-6
G. O. Odu, “Weighting methods for multi-criteria decision making technique,” Journal of Applied Sciences and Environmental Management, vol. 23, no. 8, p. 1449, Sep. 2019, https://doi.org/10.4314/jasem.v23i8.7
C. Z. Radulescu, M. Radulescu, and R. Boncea, “A Multi-Criteria Decision Support and Application to the Evaluation of the Fourth Wave of COVID-19 Pandemic,” Entropy, vol. 24, no. 5, p. 642, May 2022, https://doi.org/10.3390/e24050642
B. Xu, W. Yang, L. Yi, D. Kong, and R. Liu, “TOPSIS model with combination weight for demand assessment of flood emergency material supplies,” AIMS Mathematics, vol. 10, no. 3, pp. 5373–5398, 2025, https://doi.org/10.3934/math.2025248
L. Ma, W. Yao, X. Dai, and R. Jia, “A New Evidence Weight Combination and Probability Allocation Method in Multi-Sensor Data Fusion,” Sensors, vol. 23, no. 2, p. 722, Jan. 2023, https://doi.org/10.3390/s23020722
B. Németh et al., “Comparison of weighting methods used in multicriteria decision analysis frameworks in healthcare with focus on low- and middle-income countries,” J Comp Eff Res, vol. 8, no. 4, pp. 195–204, Apr. 2019, https://doi.org/10.2217/cer-2018-0102
E. Aydoğdu, B. Aldemir, E. Güner, and H. Aygün, “A Novel Entropy Measure with its Application to the COPRAS Method in Complex Spherical Fuzzy Environment,” Informatica, pp. 679–711, Nov. 2023, https://doi.org/10.15388/23-INFOR539
B. Ayan, S. Abacıoğlu, and M. P. Basilio, “A Comprehensive Review of the Novel Weighting Methods for Multi-Criteria Decision-Making,” Information, vol. 14, no. 5, p. 285, May 2023, https://doi.org/10.3390/info14050285
N. H. Zardari, K. Ahmed, S. M. Shirazi, and Z. Bin Yusop, Weighting Methods and their Effects on Multi-Criteria Decision Making Model Outcomes in Water Resources Management. Cham: Springer International Publishing, 2015. https://doi.org/10.1007/978-3-319-12586-2
B. Meng and G. Chi, “New Combined Weighting Model Based on Maximizing the Difference in Evaluation Results and Its Application,” Math Probl Eng, vol. 2015, pp. 1–9, 2015, https://doi.org/10.1155/2015/239634
W. Chen and X. Hao, “An Optimal Combination Weights Method Considering Both Subjective and Objective Weight Information in Power Quality Evaluation,” 2011, pp. 97–105. https://doi.org/10.1007/978-3-642-19712-3_12
S. A. Khan, M. A. Siddiqui, Z. A. Khan, M. Asjad, and S. Husain, “Numerical investigation and implementation of the Taguchi based entropy-ROV method for optimization of the operating and geometrical parameters during natural convection of hybrid nanofluid in annuli,” International Journal of Thermal Sciences, vol. 172, p. 107317, Feb. 2022, https://doi.org/10.1016/j.ijthermalsci.2021.107317
M. Keshavarz-Ghorabaee, M. Amiri, E. K. Zavadskas, Z. Turskis, and J. Antucheviciene, “Determination of Objective Weights Using a New Method Based on the Removal Effects of Criteria (MEREC),” Symmetry (Basel), vol. 13, no. 4, p. 525, Mar. 2021, https://doi.org/10.3390/sym13040525
F. Ecer and D. Pamucar, “A novel LOPCOW‐DOBI multi‐criteria sustainability performance assessment methodology: An application in developing country banking sector,” Omega (Westport), vol. 112, p. 102690, Oct. 2022, https://doi.org/10.1016/j.omega.2022.102690
A. R. Krishnan, M. M. Kasim, R. Hamid, and M. F. Ghazali, “A Modified CRITIC Method to Estimate the Objective Weights of Decision Criteria,” Symmetry (Basel), vol. 13, no. 6, p. 973, May 2021, https://doi.org/10.3390/sym13060973
Z. Gligorić, M. Gligorić, I. Miljanović, S. Lutovac, and A. Milutinović, “Assessing Criteria Weights by the Symmetry Point of Criterion (Novel SPC Method)–Application in the Efficiency Evaluation of the Mineral Deposit Multi-Criteria Partitioning Algorithm,” Computer Modeling in Engineering & Sciences, vol. 136, no. 1, pp. 955–979, 2023, https://doi.org/10.32604/cmes.2023.025021
P. Valentinas, Z. Edmundas Kazimieras, and P. Askoldas, “An Extension of the New Objective Weight Assessment Methods CILOS and IDOCRIW to Fuzzy MCDM,” Econ Comput Econ Cybern Stud Res, vol. 54, no. 2/2020, pp. 59–75, Jun. 2020, https://doi.org/10.24818/18423264/54.2.20.04
A. R. Paramanik, S. Sarkar, and B. Sarkar, “OSWMI: An objective-subjective weighted method for minimizing inconsistency in multi-criteria decision making,” Comput Ind Eng, vol. 169, p. 108138, Jul. 2022, https://doi.org/10.1016/j.cie.2022.108138
R. Kumar et al., “Revealing the benefits of entropy weights method for multi-objective optimization in machining operations: A critical review,” Journal of Materials Research and Technology, vol. 10, pp. 1471–1492, Jan. 2021, https://doi.org/10.1016/j.jmrt.2020.12.114
S. H. Mian, K. Moiduddin, H. Alkhalefah, M. H. Abidi, F. Ahmed, and F. H. Hashmi, “Mechanisms for Choosing PV Locations That Allow for the Most Sustainable Usage of Solar Energy,” Sustainability, vol. 15, no. 4, p. 3284, Feb. 2023, https://doi.org/10.3390/su15043284
A. Ristono, “Proximity Index Value for Supplier Selection Using Compromise Weighting of Stepwise Weight Assessment Ratio Analysis (SWARA) Analytical Hierarchy Process (AHP) and MEREC: A Case Study in Indonesian Leather Industry,” Journal of Applied Engineering and Technological Science (JAETS), vol. 6, no. 1, pp. 480–498, Dec. 2024, https://doi.org/10.37385/jaets.v6i1.6030
B. Paradowski, A. Shekhovtsov, A. Bączkiewicz, B. Kizielewicz, and W. Sałabun, “Similarity Analysis of Methods for Objective Determination of Weights in Multi-Criteria Decision Support Systems,” Symmetry (Basel), vol. 13, no. 10, p. 1874, Oct. 2021, https://doi.org/10.3390/sym13101874
M. Danielson and L. Ekenberg, “A Robustness Study of State-of-the-Art Surrogate Weights for MCDM,” Group Decis Negot, vol. 26, no. 4, pp. 677–691, Jul. 2017, https://doi.org/10.1007/s10726-016-9494-6
J. J. Thakkar, “Stepwise Weight Assessment Ratio Analysis (SWARA),” 2021, pp. 281–289. https://doi.org/10.1007/978-981-33-4745-8_16
I. Shafi, M. S. Farooq, I. De La Torre Díez, J. Breñosa, J. C. M. Espinosa, and I. Ashraf, “Design and Development of Smart Weight Measurement, Lateral Turning and Transfer Bedding for Unconscious Patients in Pandemics,” Healthcare, vol. 10, no. 11, p. 2174, Oct. 2022, https://doi.org/10.3390/healthcare10112174
A. Ulutaş, G. Popovic, D. Stanujkic, D. Karabasevic, E. K. Zavadskas, and Z. Turskis, “A New Hybrid MCDM Model for Personnel Selection Based on a Novel Grey PIPRECIA and Grey OCRA Methods,” Mathematics, vol. 8, no. 10, p. 1698, Oct. 2020, https://doi.org/10.3390/math8101698
R. Wardany and Z. Zahedi, “A study comparative of PSI, PSI-TOPSIS, and PSI-MABAC methods in analyzing the financial performance of state-owned enterprises companies listed on the Indonesia stock exchange,” Yugoslav Journal of Operations Research, vol. 35, no. 2, pp. 313–330, 2025, https://doi.org/10.2298/YJOR240115017W
M. A. Hatefi, “An Improved Rank Order Centroid Method (IROC) for Criteria Weight Estimation: An Application in the Engine/Vehicle Selection Problem,” Informatica, pp. 249–270, Jan. 2023, https://doi.org/10.15388/23-INFOR507
S. Zakeri, D. Konstantas, P. Chatterjee, and E. K. Zavadskas, “Soft cluster-rectangle method for eliciting criteria weights in multi-criteria decision-making,” Sci Rep, vol. 15, no. 1, p. 284, Jan. 2025, https://doi.org/10.1038/s41598-024-81027-4
H.-J. Shyur, “Combination weighting method using Z-numbers for multi-criteria decision-making,” Appl Soft Comput, vol. 174, p. 112992, Apr. 2025, https://doi.org/10.1016/j.asoc.2025.112992
D. Pamucar, F. Ecer, Z. Gligorić, M. Gligorić, and M. Deveci, “A Novel WENSLO and ALWAS Multicriteria Methodology and Its Application to Green Growth Performance Evaluation,” IEEE Trans Eng Manag, vol. 71, pp. 9510–9525, 2024, https://doi.org/10.1109/TEM.2023.3321697
J. Więckowski, B. Kizielewicz, A. Shekhovtsov, and W. Sałabun, “RANCOM: A novel approach to identifying criteria relevance based on inaccuracy expert judgments,” Eng Appl Artif Intell, vol. 122, p. 106114, Jun. 2023, https://doi.org/10.1016/j.engappai.2023.106114
A. D. A. Mandil, M. M. Salih, and Y. R. Muhsen, “Opinion Weight Criteria Method (OWCM): A New Method for Weighting Criteria With Zero Inconsistency,” IEEE Access, vol. 12, pp. 5605–5616, 2024, https://doi.org/10.1109/ACCESS.2024.3349472
M. Žižović and D. Pamučar, “New model for determining criteria weights: Level Based Weight Assessment (LBWA) model,” Decision Making: Applications in Management and Engineering, vol. 2, no. 2, Oct. 2019, https://doi.org/10.31181/dmame1902102z
F. Yin, L. Lu, J. Chai, and Y. Yang, “Combination Weighting Method Based on Maximizing Deviations and Normalized Constraint Condition,” International Journal of Security and Its Applications, vol. 10, no. 2, pp. 39–50, Feb. 2016, https://doi.org/10.14257/ijsia.2016.10.2.04
F. Cai, Z. Hu, B. Jiang, W. Ruan, S. Cai, and H. Zou, “Ecological Health Assessment with the Combination Weight Method for the River Reach after the Retirement and Renovation of Small Hydropower Stations,” Water (Basel), vol. 15, no. 2, p. 355, Jan. 2023, https://doi.org/10.3390/w15020355
W. Cheng et al., “Improved Combination Weighted Prediction Model of Aquifer Water Abundance Based on a Cloud Model,” ACS Omega, vol. 7, no. 40, pp. 35840–35850, Oct. 2022, https://doi.org/10.1021/acsomega.2c04162
B. Zhao, Y.-B. Shao, C. Yang, and C. Zhao, “The application of the game theory combination weighting-normal cloud model to the quality evaluation of surrounding rocks,” Front Earth Sci (Lausanne), vol. 12, Apr. 2024, https://doi.org/10.3389/feart.2024.1346536
Z. Li, Z. Fan, and S. Shen, “Urban Green Space Suitability Evaluation Based on the AHP-CV Combined Weight Method: A Case Study of Fuping County, China,” Sustainability, vol. 10, no. 8, p. 2656, Jul. 2018, https://doi.org/10.3390/su10082656
L. Hongjiu and H. Yanrong, “An Evaluating Method with Combined Assigning-Weight Based on Maximizing Variance,” Sci Program, vol. 2015, pp. 1–8, 2015, https://doi.org/10.1155/2015/290379
Z. Li, Z. Fan, and S. Shen, “Urban Green Space Suitability Evaluation Based on the AHP-CV Combined Weight Method: A Case Study of Fuping County, China,” Sustainability, vol. 10, no. 8, p. 2656, Jul. 2018, https://doi.org/10.3390/su10082656
S. Zha, Y. Guo, S. Huang, and S. Wang, “A Hybrid MCDM Method Using Combination Weight for the Selection of Facility Layout in the Manufacturing System: A Case Study,” Math Probl Eng, vol. 2020, pp. 1–16, Feb. 2020, https://doi.org/10.1155/2020/1320173
D. Tešić and D. Marinković, “Application of fermatean fuzzy weight operators and MCDM model DIBR-DIBR II-NWBM-BM for efficiency-based selection of a complex combat system,” Journal of Decision Analytics and Intelligent Computing, vol. 3, no. 1, pp. 243–256, Dec. 2023, https://doi.org/10.31181/10002122023t
H. R. Kolour, V. Momayezi, and F. Momayezi, “Enhancing Supplier Selection in Public Manufacturing: A Hybrid Multi-Criteria Decision-Making Approach,” Spectrum of Decision Making and Applications, vol. 3, no. 1, pp. 1–20, Mar. 2025, https://doi.org/10.31181/sdmap31202629
T. Jameel, Y. Yasin, and M. Riaz, “An Integrated Hybrid MCDM Framework for Renewable Energy Prioritization in Sustainable Development,” Spectrum of Decision Making and Applications, vol. 3, no. 1, pp. 124–150, May 2025, https://doi.org/10.31181/sdmap31202640
A. Puška, M. Nedeljković, D. Pamučar, D. Božanić, and V. Simić, “Application of the new simple weight calculation (SIWEC) method in the case study in the sales channels of agricultural products,” MethodsX, vol. 13, p. 102930, Dec. 2024, https://doi.org/10.1016/j.mex.2024.102930
M. Nedeljković, Z. Papović, and S. Krstić, “Assessment of the weight of factors influencing food losses using fuzzy multi-criteria analysis,” Ekonomika poljoprivrede, vol. 71, no. 4, pp. 1313–1324, Dec. 2024, https://doi.org/10.59267/ekoPolj24041313N
M. Nedeljković and S. Vujičić, “Evaluation of sustainable agricultural tourism criteria,” in Climate changes and ecological sustainability in agriculture and food production in Serbia, the region and Southeastern Europe : proceedings, Association science and business center WORLD; Institute for plant protection and environmen, 2025, pp. 250–256. https://doi.org/10.46793/MAK2025.250N
M. Nedeljković, D. Božanić, A. Štilić, Y. R. Muhsen, and A. Puška, “Evaluation of agricultural drones based on the COmpromise Ranking from Alternative SOlutions (CORASO) methodology,” Engineering review, vol. 44, no. 4, pp. 77–90, 2024, https://doi.org/10.30765/er.2653
Adis Puška, Darko Božanić, Anđelka Štilić, Miroslav Nedeljković, and Mohammad Khalilzadeh, “Application of Fuzzy-Rough Methodology to the Selection of Electric Tractors for Small Farms in Semberija,” Journal of Fuzzy Extension and Applications, vol. 6, no. 4, pp. 651–668, 2025. https://doi.org/10.22105/jfea.2025.482890.1663
Huihui Gao and Kun Qian, “Risk Assessment of Municipal Water Supply and Drainage Project Costs Using Neutrosophic Numbers,” Neutrosophic Sets and Systems, vol. 81, pp. 712–728, 2025. https://doi.org/10.5281/zenodo.14897148
I. K. A. El-Jaberi, I. Stojanović, A. Puška, N. Ljepava, and R. Prodanović, “Selection of Renewable Energy Projects from the Investor’s Point of View Based on the Fuzzy–Rough Approach and the Bonferroni Mean Operator,” Sustainability, vol. 16, no. 22, p. 9929, Nov. 2024, https://doi.org/10.3390/su16229929
A. Katrancı, N. Kundakcı, and K. Arman, “Fuzzy SIWEC and Fuzzy RAWEC Methods for Sustainable Waste Disposal Technology Selection,” Spectrum of Operational Research, vol. 3, no. 1, pp. 87–102, Apr. 2025, https://doi.org/10.31181/sor31202633
R. V. Rao and J. Lakshmi, “R-method: A simple ranking method for multi-attribute decision-making in the industrial environment,” Journal of Project Management, pp. 223–230, 2021, https://doi.org/10.5267/j.jpm.2021.5.001
S. Chatterjee and S. Chakraborty, “Application of the R method in solving material handling equipment selection problems,” Decision Making: Applications in Management and Engineering, vol. 6, no. 2, pp. 74–94, Oct. 2023, https://doi.org/10.31181/dmame622023391
B. Kizielewicz and A. Bączkiewicz, “Comparison of Fuzzy TOPSIS, Fuzzy VIKOR, Fuzzy WASPAS and Fuzzy MMOORA methods in the housing selection problem,” Procedia Comput Sci, vol. 192, pp. 4578–4591, 2021, https://doi.org/10.1016/j.procs.2021.09.236
P. Aazagreyir, P. Appiahene, O. Appiah, and S. Boateng, “Comparative analysis of fuzzy multi-criteria decision-making methods for quality of service-based web service selection,” IAES International Journal of Artificial Intelligence (IJ-AI), vol. 13, no. 2, p. 1408, Jun. 2024, https://doi.org/10.11591/ijai.v13.i2.pp1408-1419
Ž. Stević, E. Durmić, M. Gajić, D. Pamučar, and A. Puška, “A Novel Multi-Criteria Decision-Making Model: Interval Rough SAW Method for Sustainable Supplier Selection,” Information, vol. 10, no. 10, p. 292, Sep. 2019, https://doi.org/10.3390/info10100292
P. Akhavan, S. Barak, H. Maghsoudlou, and J. Antuchevičienė, “FQSPM-SWOT for strategic alliance planning and partner selection; Case study in a holding car manufacturer company,” Technological and Economic Development of Economy, vol. 21, no. 2, pp. 165–185, Mar. 2015, https://doi.org/10.3846/20294913.2014.965240
S. Mufazzal and S. M. Muzakkir, “A new multi-criterion decision making (MCDM) method based on proximity indexed value for minimizing rank reversals,” Comput Ind Eng, vol. 119, pp. 427–438, May 2018, https://doi.org/10.1016/j.cie.2018.03.045
A. Sotoudeh-Anvari, “Root Assessment Method (RAM): A novel multi-criteria decision making method and its applications in sustainability challenges,” J Clean Prod, vol. 423, p. 138695, Oct. 2023, https://doi.org/10.1016/j.jclepro.2023.138695
H. B. Mann and D. R. Whitney, “On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other,” The Annals of Mathematical Statistics, vol. 18, no. 1, pp. 50–60, Mar. 1947, https://doi.org/10.1214/aoms/1177730491
E. Şimşek, S. Eti, S. Yüksel, and H. Dinçer, “Evaluation of Purchasing Process in Solar Energy Investment Projects via SIWEC Methodology,” Spectrum of Operational Research, vol. 3, no. 1, pp. 81–86, Apr. 2025, https://doi.org/10.31181/sor31202636
A. Katrancı, N. Kundakcı, and K. Arman, “Fuzzy SIWEC and Fuzzy RAWEC Methods for Sustainable Waste Disposal Technology Selection,” Spectrum of Operational Research, vol. 3, no. 1, pp. 87–102, Apr. 2025, https://doi.org/10.31181/sor31202633




