Hybrid Solution (HybSo) Based on Hybrids Normalization and Aggregation for the Multi-Criteria Decision-Making Problems
Abstract
Real-world decision making problems often dictates to take into account several point of view that are objectively conflictuel. Many studies were dedicated to provide decision makers with methods for solving this type of highly complex problems. In this paper, we propose a new hybrid multi-criteria decision making method with a new hybrid normalization and aggregation strategies. Mainly, the proposed method introduces a new hybrid normalization between the distance measure and the ratio system, and also uses two hybrid equations to compute the weighted performance of alternatives as to improve the stability of the method and the flexibility of the results. Moreover, hybrid aggregation rule based on exponential and logarithmic functions is proposed to establish the final ranking of the alternatives. To assess the performance of the proposed method, we used two real problems: the logistic provider selection problem and the evaluation of microclimate in an office problem. Comparative results with eight state-of-the-art multicriteria decision making methods and sensitivity analysis established its validity, in terms of performance and stability, for solving multi-criteria decision making problems.
References
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C. L. HwangandK.Yoon, Multiple Attribute Decision Making. Economics and Mathematical Systems. Springer: Berlin, Germany, 1981.
E. K.Zavadskas and Z. Turskis, “A new additive ratio assessment (ARAS) method in multicriteria decision-making,” Technological and economic development of economy, vol. 16, no. 2, pp. 159–172, 2010.
A. Alinezhad and J. Khalili, New methods and applications in multiple attribute decision making (MADM). Springer, 2019, vol. 277.
M.Keshavarz Ghorabaee, E. K. Zavadskas, Z. Turskis, and J. Antucheviciene, “A new combinative distance-based assessment (CODAS) method for multi-criteria decision-making.” Economic Computation & Economic Cybernetics Studies & Research, vol. 50, no. 3, 2016.
J. Gao, F. Guo, Z. Ma, and X. Huang, “Multi-criteria decision-making framework for largescale rooftop photovoltaic project site selection based on intuitionistic fuzzy sets,” Applied Soft Computing, vol. 102, p. 107098, 2021.
R. N. Wardany and 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, 2024. doi: 10.2298/YJOR240115017W
S. Gumus, G. Egilmez, M. Kucukvar, and Y. Shin Park, “Integrating expert weighting and multi-criteria decision making into eco-efficiency analysis: the case of US manufacturing,” Journal of the Operational Research Society, vol. 67, no. 4, pp. 616–628, 2016-04. doi: 10.1057/jors.2015.88
J. A. Annema, N. Mouter, and J. Razaei, “Cost-benefit analysis (CBA), or multicriteria decision-making (MCDM) or both: Politiciansˆ a perspective in transport policy appraisal,” Transportation Research Procedia, vol. 10, pp. 788–797, 2015-01-01. doi: 10.1016/j.trpro.2015.09.032
M. K. Mehlawat, “Behavioral optimization models for multicriteria portfolio selection,” Yugoslav Journal of Operations Research, vol. 23, no. 2, pp. 279–297, 2013. doi: 10.2298/YJOR130304028M
C. Jatoth, G. R. Gangadharan, U. Fiore, and R. Buyya, “SELCLOUD: a hybrid multi-criteria decision-making model for selection of cloud services,” Soft Computing, vol. 23, no. 13, pp. 4701–4715, 2019.
S. Biswas, D. Kumar, M. Nas, M. Softa, E. Akg¨ un, and U. K. Bera, “Performance of a fivelayer ANN model for earthquake magnitude prediction and spatial risk mapping in turkey,” Decision Making Advances, vol. 3, no. 1, pp. 40–49. doi: 10.31181/dma31202553
M. Radovanovi´¸, A. Petrovski, E. Cirkin, A. Behli´c, v. Joki´c, D. Chemezov, E. G. Hashimov, M. B. Bouraima, and C. Jana, “Application of the new hybrid model LMAW-g-EDAS multi-criteria decision-making when choosing an assault rifle for the needs of the army,” Journal of Decision Analytics and Intelligent Computing, vol. 4, no. 1, pp. 16–31. doi: 10.31181/jdaic10021012024r
K. H. Gazi, N. Raisa, A. Biswas, F. Azizzadeh, and S. P. Mondal, “Finding the most important criteria in women’s empowerment for sports sector by pentagonal fuzzy DEMATEL methodology,” Spectrum of Decision Making and Applications, vol. 2, no. 1, pp. 28–52. doi: 10.31181/sdmap21202510
A. Jain, P. Sharma, S. Saleh, T. Dolai, S. Saha, R. Bagga, A. Khadwal, A. Trehan, I. Nielsen, A. Kaviraj, R. Das, and S. Saha, “Multi-criteria decision making to validate performance of RBC-based formulae to screen β-thalassemia trait in heterogeneous haemoglobinopathies,” BMC Medical Informatics and Decision Making, vol. 24, no. 1, p. 5. doi: 10.1186/s12911023-02388-w
R. Kumar, “Multi-criteria decision-making applications in agro-based industries for economic development: An overview of global trends, collaborative patterns, and research gaps,” Spectrum of Engineering and Management Sciences, vol. 2, no. 1, pp. 247–262. doi: 10.31181/sems21202431k
R. Salehzadeh and M. Ziaeian, “Decision making in human resource management: a systematic review of the applications of analytic hierarchy process,” Frontiers in Psychology, vol. 15. doi: 10.3389/fpsyg.2024.1400772
T. Berˇciˇ c, M. Bohanec, and L. Aˇ zman Momirski, “Integrating multi-criteria decision models in smart urban planning: A case study of architectural and urban design competitions,” Smart Cities, vol. 7, no. 2, pp. 786–805. doi: 10.3390/smartcities7020033
M. Heidarisoltanabadi, B. Elhami, A. Imanmehr, and A. Khadivi, “Determination of the most appropriate fertilizing method for apple trees using multi-criteria decision-making (MCDM) approaches,” Food Science & Nutrition, vol. 12, no. 2, pp. 1158–1169. doi: 10.1002/fsn3.3831
B. Jurkowska, “The federal states of germanyˆ aanalysis and measurement of development using taxonomic methods,” Oeconomia Copernicana, vol. 5, no. 3, pp. 49–73, 2014.
H.-H. Wu and Y.-N. Tsai, “A dematel method to evaluate the causal relations among the criteria in auto spare parts industry,” Applied Mathematics and Computation, vol. 218, no. 5, pp. 2334–2342, 2011.
J. H. Paelinck, “Qualiflex: a flexible multiple-criteria method,” Economics Letters, vol. 1, no. 3, pp. 193–197, 1978.
M. Wang, S.-J. Lin, and Y.-C. Lo, “The comparison between MAUT and PROMETHEE,” in 2010 IEEE international conference on industrial engineering and engineering management. IEEE, 2010, pp. 753–757.
M. Roubens, “Preference relations on actions and criteria in multicriteria decision making,” European Journal of Operational Research, vol. 10, no. 1, pp. 51–55, 1982.
P. Chatterjee, V. M. Athawale, and S. Chakraborty, “Materials selection using complex proportional assessment and evaluation of mixed data methods,” Materials & Design, vol. 32, no. 2, pp. 851–860, 2011-02-01. doi: 10.1016/j.matdes.2010.07.010
E. Hinloopen and P. Nijkamp, “Regime-methods voor ordinal multicriteria-analyses,” Kwantitatieve Methoden, vol. 7, no. 22, pp. 61–78, 1986.
J.-P. Brans and Y. De Smet, “Promethee methods,” in Multiple Criteria Decision Analysis: State of the Art Surveys, J. Figueira, S. Greco, and M. Ehrgott, Eds. New York, NY: Springer New York, 2005, pp. 187–219.
W. Edwards and F. H. Barron, “SMARTS and SMARTER: Improved simple methods for multiattribute utility measurement,” Organizational behavior and human decision processes, vol. 60, no. 3, pp. 306–325, 1994.
J. R. Figueira, V. Mousseau, and B. Roy, “ELECTRE methods,” in Multiple criteria decision analysis. Springer, 2016, pp. 155–185.
F. A. F. Ferreira and S. P. Santos, “Two decades on the macbeth approach: a bibliometric analysis,” Annals of Operations Research, vol. 296, no. 1, pp. 901–925, 2021-01-01. doi: 10.1007/s10479-018-3083-9
F. Alali and A. C. Tolga, “Portfolio allocation with the TODIM method,” Expert Systems with Applications, vol. 124, pp. 341–348, 2019.
N. M. Stefano, N. Casarotto Filho, L. G. L. Vergara, and R. U. G. da Rocha, “COPRAS (complex proportional assessment): state of the art research and its applications,” IEEE Latin America Transactions, vol. 13, no. 12, pp. 3899–3906, 2015.
D.Diakoulaki, G. Mavrotas, and L. Papayannakis, “Determining objective weights in multiple criteria problems: The critic method,” Computers & Operations Research, vol. 22, no. 7, pp. 763–770, 1995-08-01. doi: 10.1016/0305-0548(94)00059-H
E.LalondeandC.Bergeron, “Adecision-support methodology for asset management,” in New Pipeline Technologies, Security, and Safety, 2003, pp. 33–43.
A. Jahan, F. Mustapha, M. Y. Ismail, S. M. Sapuan, and M. Bahraminasab, “A comprehensive VIKOR method for material selection,” Materials & Design, vol. 32, no. 3, pp. 1215–1221, 2011.
X. Xu, “The sir method: A superiority and inferiority ranking method for multiple criteria decision making,” European journal of operational research, vol. 131, no. 3, pp. 587–602, 2001.
W.K.Brauers and E. K. Zavadskas, “The MOORAmethodandits application to privatization in a transition economy,” Control and cybernetics, vol. 35, no. 2, pp. 445–469, 2006.
J. J. Thakkar, “Stepwise weight assessment ratio analysis (SWARA),” in Multi-Criteria Decision Making. Springer, 2021, pp. 281–289.
E. K. Zavadskas, J. Antucheviciene, S. H. Razavi Hajiagha, and S. S. Hashemi, “Extension of weighted aggregated sum product assessment with interval-valued intuitionistic fuzzy numbers (WASPAS-IVIF),” Applied Soft Computing, vol. 24, pp. 1013–1021, 2014-11-01. doi: 10.1016/j.asoc.2014.08.031
A. Krylovas, E. K. Zavadskas, N. Kosareva, and S. Dadelo, “New KEMIRA method for determining criteria priority and weights in solving MCDM problem,” International Journal of Information Technology & Decision Making, vol. 13, no. 6, pp. 1119–1133, 2014-11. doi: 10.1142/S0219622014500825
M. Keshavarz Ghorabaee, E. K. Zavadskas, L. Olfat, and Z. Turskis, “Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (EDAS),” Informatica, vol. 26, no. 3, pp. 435–451, 2015-01-01. doi: 10.3233/INF-2015-1070
D. Pamucar and G. Cirovic, “The selection of transport and handling resources in logistics centers using multi-attributive border approximation area comparison (MABAC),” Expert Systems with Applications, vol. 42, no. 6, pp. 3016–3028, 2015-04-15. doi: 10.1016/j.eswa.2014.11.057
E. K. Zavadskas and V. Podvezko, “Integrated determination of objective criteria weights in MCDM,”International Journal of Information Technology & Decision Making, vol. 15, no. 2, pp. 267–283, 2016-03. doi: 10.1142/S0219622016500036
M. Jakˇ si´ c, P. Mimovi´c, and M. Lekovi´ c, “A multicriteria decision making approach to performance evaluation of mutua funds: A case study in serbia,” Yugoslav Journal of Operations Research, vol. 28, no. 3, pp. 385–414. doi: 10.2298/YJOR170217023J
D. S. Pamuˇ car, G. ´ Cirovi´ c, and D. Boˇzani´ c, “Application of interval valued fuzzy-rough numbers in multi-criteria decision making: The IVFRN-MAIRCA model,” Yugoslav journal of operations research, vol. 29, no. 2, pp. 221–247. doi: 0.2298/YJOR180415011P
S.-P. Wan, J.-Y. Dong, and S.-M. Chen, “An integrated method for shared power bank supplier selection based on linguistic hesitant fuzzy multi-criteria group decision making,” KnowledgeBased Systems, vol. 301, p. 112300. doi: 10.1016/j.knosys.2024.112300
S.-P. Wan, C.-y. Zeng, J.-y. Dong, and S.-s. Hu, “Linguistic hesitant fuzzy interactive multiattribute group decision making for enterprise resource planning selection,” Journal of Management Analytics, vol. 11, no. 3, pp. 389–444. doi: 10.1080/23270012.2024.2371517
S.-P. Wan, J.-Y. Dong, and Z.-H. Zhang, “Two-stage consensus reaching process in social network large group decision-making with application to battery supplier selection,” Information Sciences, vol. 668, p. 120526. doi: 10.1016/j.ins.2024.120526
S.-P. Wan, J.-Y. Dong, and S.-M. Chen, “A novel intuitionistic fuzzy best-worst method for group decision making with intuitionistic fuzzy preference relations,” Information Sciences, vol. 666, p. 120404. doi: 10.1016/j.ins.2024.120404
S.-P. Wan, S.-Z. Gao, and J.-Y. Dong, “Trapezoidal cloud based heterogeneous multi-criterion group decision-making for container multimodal transport path selection,” Applied Soft Computing, vol. 154, p. 111374. doi: 10.1016/j.asoc.2024.111374
S.-P. Wan, H. Wu, and J.-Y. Dong, “An integrated method for complex heterogeneous multi-attribute group decision-making and application to photovoltaic power station site selection,” Expert Systems with Applications, vol. 242, p. 122456. doi: 10.1016/j.eswa.2023.122456
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Published
2025-07-17
How to Cite
DJEDDI, Youcef.
Hybrid Solution (HybSo) Based on Hybrids Normalization and Aggregation for the Multi-Criteria Decision-Making Problems.
Yugoslav Journal of Operations Research, [S.l.], july 2025.
ISSN 2334-6043.
Available at: <https://yujor.fon.bg.ac.rs/index.php/yujor/article/view/1353>. Date accessed: 19 july 2025.
doi: https://doi.org/10.2298/YJOR241020020D.
Issue
Section
Research Articles
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
