Comparative Study of the Selection of the Best Contractor Using Fuzzy Weak Autocatalytic Set and Analytic Hierarchy Process
Keywords:
Analytic Hierarchy Process, Contractor Selection, Fuzzy Weak Autocatalytic, Multi-criteria Decision-Making, Sensitivity AnalysisAbstract
The prevalence of pairwise comparison in decision-making processes, particularly in Multiple Criteria Decision Making (MCDM) contexts, and the need for effective techniques to address MCDM challenges in the context of contractor selection. The objectives of this research are; 1) To explore and apply the Fuzzy Weak Autocatalytic Set (FWACS) technique in the problem of contractor selection. 2) To compare the outcomes of FWACS with those obtained using the Analytic Hierarchy Process (AHP). This research has been initiated by a preliminary analysis of the characteristics of the theorem based on a literature review. The methodology will start with the utilization of the FWACS technique, followed by the conception of a fuzzy graph through a comparative assessment of a set of alternatives. Next is a comprehensive comparison of outcomes between FWACS and the Analytic Hierarchy Process (AHP), and lastly, a sensitivity analysis to substantiate the stability and consistency of decisions derived from FWACS. The decisions derived from FWACS exhibit stability and consistency. In comparison with AHP, it's confirmed that FWACS not only matches established methods but also excels in handling uncertainties typical of real-world situations. FWACS, especially within the fuzzy framework, stands out for effectively managing uncertainty. This advantage makes it particularly useful for complex decision problems involving imprecise or ambiguous information. The practical application of FWACS in addressing contractor selection problems. The substantiated stability and consistency of decisions derived from FWACS make them comparable to those derived from AHP.
References
H. Taherdoost and M. Madanchian, “Multi-criteria decision making (MCDM) methods and
concepts,” Encyclopedia, vol. 3, no. 1, pp. 77–87, Jan. 2023, doi:
3390/encyclopedia3010006.
S. K. Sahoo and S. S. Goswami, “A comprehensive review of multiple criteria decision-making
(MCDM) methods: Advancements, applications, and future directions,” Decis. Mak. Adv., vol.
, no. 1, pp. 25–48, June 2023, doi: 10.31181/dma1120237.
N. Rane, A. Achari, and S. Choudhary, “Multi-criteria decision-making (MCDM) as a powerful
tool for sustainable development: Effective applications of AHP, FAHP, TOPSIS, ELECTRE,
and VIKOR in sustainability,” Int. Res. J. Mod. Eng. Technol. Sci., vol. 5, no. 4, pp. 2654-
, Apr. 2023, doi: 10.56726/irjmets36215.
L. Čaklović and A. S. Kurdija, “A universal voting system based on the Potential Method,” Eur.
J. Oper. Res., vol. 259, no. 2, pp. 677–688, June 2017, doi: 10.1016/j.ejor.2016.10.032.
S. S. Mamat, T. Ahmad, S. R. Awang, and N. Ahmad, “The application of fuzzy weak
autocatalytic set in robots kinematic structures evaluation,” ASM Sc. J., vol. 18, Sep. 2023,
doi: 10.32802/asmscj.2023.1414.
S. Jain and S. Krishna, “Emergence and growth of complex networks in adaptive systems,”
Comput. Phys. Commun., vol. 121, pp. 116–121, 1999, doi: 10.1016/S0010-4655(99)00293-
L. Čaklović and V. Šego, “Potential Method Applied on Exact Data,” in The Proceedings of
th International Conference on Operational Research KOI, 2002, pp. 237–248.
M. Balubaid and R. Alamoudi, “Application of the analytical hierarchy process (AHP) to multicriteria analysis for contractor selection,” Am. J. Ind. Bus. Manag., vol. 5, no. 9, pp. 581–589,
Sep. 2015, doi: 10.4236/ajibm.2015.59058.
J. C Xavier, W. Hordijk, S. Kauffman, M. Steel, and W. F Martin, “Autocatalytic Chemical
Networks at the Origin of Metabolism,” in The Proceedings of the Royal Society B: Biological
Sciences, vol. 287, no. 1922, pp. 20192377, 2020, doi: 10.1098/rspb.2019.2377.
S. Jain and S. Krishna, “Autocatalytic sets and the growth of complexity in an evolutionary
model,” Phys. Rev. Lett., vol. 81, no. 25, pp. 5684, Dec. 1998, doi:
1103/PhysRevLett.81.5684.
S. S. Mamat, T. Ahmad, S. R. Awang, and M. Z. Mukaram, “Ranking by Fuzzy Weak
Autocatalytic Set,” in The Proceedings of the 4th International Conference on Soft Computing
in Data Science, Bangkok, Thailand, 2018. Singapore: Springer, 2019, vol. 937, pp. 161–172.
https://doi.org/10.1007/978-981-13-3441-2_13
S. S. Mamat, S. R. Awang, and T. Ahmad, “Preference graph of potential method as a fuzzy
graph,” Advances in Fuzzy Systems, vol. 2020, pp. 1–14, Feb. 2020. doi:
1155/2020/8697890.
A. Tabraiz, Z. S. Mufti, M. N. Aslam, N. Saleem, and H. Hosseinzadeh, “Fuzzy computational
analysis of flower graph via fuzzy topological indices,” J. Math., vol. 2023, pp. 1–8, Aug. 2023.
doi: 10.1155/2023/8077729
S. A. Bakar, N. S. M. Noor, T. Ahmad, and S. S. Mamat, “Bounded autocatalytic set and its
basic properties,” Mathematics and Statistics, vol. 11, no. 3, pp. 558–565, 2023. doi:
13189/ms.2023.110312.
A. Ishizaka and S. Siraj, “Interactive consistency correction in the analytic hierarchy process
to preserve ranks,” Decis. Econ. Finance, vol. 43, no. 2, pp. 443–464, 2020, doi:
1007/s10203-020-00309-4
J. Wiȩckowski and W. Sałabun, “Sensitivity analysis approaches in multi-criteria decision
analysis: A systematic review,” Appl. Soft Comput., vol. 148, 2023. doi:
1016/j.asoc.2023.110915.
S. Singh, S. Bhattacharya, and V. Saddikuti, “An application of AHP and fuzzy AHP with
sensitivity analysis for selecting the right process to impart knowledge,” Int. J. Knowl. Manag.
Stud., vol. 11, no. 3, pp. 258–277, 2020. doi: 10.1504/IJKMS.2020.109091.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Siti Salwana Mamat, Zarith Sofiah Othman, Noraini Ahmad
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
