Advanced Fuzzy-Based Decision-Making: The Linear Diophantine Fuzzy CODAS Method for Logistic Specialist Selection

Jeevitha Kannan; Vimala Jayakumar; Mahalakshmi Pethaperumal

doi:10.31181/sor2120259

Authors

Jeevitha Kannan Department of Mathematics, Alagappa University, Karaikudi, India Author https://orcid.org/0000-0001-7846-9173
Vimala Jayakumar Department of Mathematics, Alagappa University, Karaikudi, India Author https://orcid.org/0000-0003-3138-9365
Mahalakshmi Pethaperumal Department of Mathematics, Alagappa University, Karaikudi, India Author https://orcid.org/0009-0000-7716-9179

DOI:

https://doi.org/10.31181/sor2120259

Keywords:

Linear Diophantine Fuzzy Set, CODAS, Logistics, Logistic Specialist

Abstract

This study addresses the inherent uncertainty in human decision-making by leveraging fuzzy sets, which were introduced to better capture the imprecision associated with human thoughts and judgments. As an extension to traditional fuzzy sets, the Linear Diophantine Fuzzy Set (LDFS) was developed, offering a more flexible approach by relaxing existing limitations on grade values. The LDFS has found applications across various fields, demonstrating its versatility and effectiveness. In this study, we explore the application of the Linear Diophantine Fuzzy Set within the framework of the Combinative Distance-based Assessment (CODAS) method. The CODAS method stands out because it incorporates Euclidean and Taxicab distances. Decision-making should consider not only the direct distances between ideal solutions and alternatives but also the indirect distances. The foremost objective of this research is to propose a novel approach by integrating the CODAS method with the LDFS to address complex decision-making problems characterized by uncertainty and imprecision. To illustrate the practical utility of the proposed method, we apply it to a numerical example involving the selection of a logistics specialist, a critical decision in emergency logistics optimization. The research also includes a case study on a logistics specialist, highlighting the practical application of the methods discussed. Furthermore, this study provides a comprehensive sensitivity analysis of the parameters' weights to evaluate the robustness and reliability of the proposed method. The results highlight the effectiveness of the LDF CODAS method in making informed and reliable decisions under conditions of uncertainty, paving the way for future applications in other decision-making scenarios.

Downloads

Download data is not yet available.

References

Chen, C. T. (2000). Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets and Systems, 114(1), 1–9. https://doi.org/10.1016/S0165-0114(97)00377-1

Afshari, A., & Kowal, J. (2017). Decision Making Methods for the Selection of ICT Project Manager. Gospodarka Rynek Edukacja= Economy Market Education, 18(4), 19-28. https://doi.org/10.2139/ssrn.3118075

Bali, Ö., Gümüş, S., & Dağdeviren, M. (2013). A group madm method for personnel selection problem using delphi technique based on intuitionistic fuzzy sets. Journal of Management and Information Science, 1(1), 1–13.

Boran, E., Genç, S., & Akay, D. (2011). Personnel selection based on intuitionistic fuzzy sets. Human Factors and Ergonomics in Manufacturing Service Industries, 21, 493–503. https://doi.org/10.1002/hfm.20252

Chen, C. T., Pai, P. F., & Hung, W. Z. (2011). Applying linguistic vikor and knowledge map in personnel selection. Asia Pacific Management Review, 16(4), 491-502.

Chaghooshi, A., Arab, A., & Dehshiri, S. (2016). A fuzzy hybrid approach for project manager selection. Decision Science Letters, 5, 447–460. https://doi.org/10.5267/j.dsl.2016.1.001

Dodangeh, J., Sorooshian, S., & Afshari, A. R. (2014). Linguistic Extension for Group Multicriteria Project Manager Selection. Journal of Applied Mathematics, 2014, 570398. https://doi.org/10.1155/2014/570398

Kelemenis, A., & Askounis, D. (2010). A new TOPSIS-based multi-criteria approach to personnel selection. Expert Systems with Applications, 37(7), 4999–5008. https://doi.org/10.1016/j.eswa.2009.12.013

Kelemenis, A., Ergazakis, K., & Askounis, D. (2011). Support managers selection using an extension of fuzzy TOPSIS. Expert Systems with Applications, 38(3), 2774–2782. https://doi.org/10.1016/j.eswa.2010.08.068

Nobari, S. M., & Zadeh, D. H. (2013). Designing a fuzzy model for decision support systems in the selection and recruitment process. African Journal of Business Management, 7(16), 1486. https://doi.org/10.5897/AJBM11.2803 *ovo ne mogu da otvorim ni da nadjem dokument, mada ga ima u goole scholar

Mahdavi, I., Mahdavi-Amiri, N., Heidarzade, A., & Nourifar, R. (2008). Designing a model of fuzzy TOPSIS in multiple criteria decision making. Applied Mathematics and Computation, 206(2), 607–617. https://doi.org/10.1016/j.amc.2008.05.047

Mammadova, M., & Jabrayilova, Z. (2014). Application of Fuzzy Optimization Method in Decision-Making for Personnel Selection. Intelligent Control and Automation, 5(4), 190–204. https://doi.org/10.4236/ica.2014.54021

Zadeh, L. (1965). Fuzzy sets. Information and Control, 8(3), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X

Atanassov, K. T. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20(1), 87–96. https://doi.org/10.1016/S0165-0114(86)80034-3

Yager, R. R. (2014). Pythagorean Membership Grades in Multicriteria Decision Making. IEEE Transactions on Fuzzy Systems, 22(4), 958–965. https://doi.org/10.1109/TFUZZ.2013.2278989

Yager, R. R. (2017). Generalized Orthopair Fuzzy Sets. IEEE Transactions on Fuzzy Systems, 25(5), 1222–1230. https://doi.org/10.1109/TFUZZ.2016.2604005

Riaz, M., & Hashmi, M. R. (2019). Linear diophantine fuzzy set and its applications towards multi-attribute decision-making problems. Journal of Intelligent & Fuzzy Systems, 37(4), 5417–5439. https://doi.org/10.3233/jifs-190550

Kannan, J., Jayakumar, V., Pethaperumal, M., & Kather Mohideen, A. B. (2024). An intensified linear diophantine fuzzy combined dematel framework for the assessment of climate crisis. Stochastic Environmental Research and Risk Assessment. https://doi.org/10.1007/s00477-023-02618-7

Jeevitha, K., Garg, H., Vimala, J., Aljuaid, H., & Abdel-Aty, A.-H. (2023). Linear diophantine multifuzzy aggregation operators and its application in digital transformation. Journal of Intelligent & Fuzzy Systems, 45(2), 3097–3107. https://doi.org/10.3233/JIFS-223844

Jayakumar, V., Mohideen, A. B. K., Saeed, M. H., Alsulami, H., Hussain, A., & Saeed, M. (2023). Development of Complex Linear Diophantine Fuzzy Soft Set in Determining a Suitable Agri-Drone for Spraying Fertilizers and Pesticides. IEEE Access, 11, 9031–9041. https://doi.org/10.1109/ACCESS.2023.3239675

Iampan, A., García, G. S., Riaz, M., Athar Farid, H. M., & Chinram, R. (2021). Linear diophantine fuzzy einstein aggregation operators for multi-criteria decision-making problems. Journal of Mathematics, 2021, 5548033. https://doi.org/10.1155/2021/5548033

Ayub, S., Shabir, M., Riaz, M., Aslam, M., & Chinram, R. (2021). Linear diophantine fuzzy relations and their algebraic properties with decision making. Symmetry, 13(6), 945. https://doi.org/10.3390/sym13060945

Riaz, M., Hashmi, M. R., Kalsoom, H., Pamucar, D., & Chu, Y. M. (2020). Linear diophantine fuzzy soft rough sets for the selection of sustainable material handling equipment. Symmetry, 12(8), 1215. https://doi.org/10.3390/sym12081215

Riaz, M., Farid, H. M. A., Aslam, M., Pamucar, D., & Bozanić, D. (2021). Novel approach for third-party reverse logistic provider selection process under linear diophantine fuzzy prioritized aggregation operators. Symmetry, 13(7), 1152. https://doi.org/10.3390/sym13071152

Farid, H. M. A., Riaz, M., Khan, M. J., Kumam, P., & Sitthithakerngkiet, K. (2022). Sustainable thermal power equipment supplier selection by einstein prioritized linear diophantine fuzzy aggregation operators. AIMS Mathematics, 7(6), 11201–11242. https://doi.org/10.3934/math2022627

Riaz, M., Farid, H. M. A., Wang, W., & Pamucar, D. (2022). Interval-valued linear diophantine fuzzy frank aggregation operators with multi-criteria decision-making. Mathematics, 10(11), 1811. https://doi.org/10.3390/math10111811

Jayakumar, V., Kannan, J., Kausar, N., Deveci, M., & Wen, X. (2024). Multicriteria group decision making for prioritizing iot risk factors with linear diophantine fuzzy sets and marcos method. Granular Computing, 9, 56. https://doi.org/10.1007/s41066-024-00480-8

Kannan, J., Jayakumar, V., Saeed, M., Alballa, T., Khalifa, H. A. E. W., & Gomaa, H. G. (2024). Linear diophantine fuzzy clustering algorithm based on correlation coefficient and analysis on logistic efficiency of food products. IEEE Access, 12, 34889–34902. https://doi.org/10.1109/access.2024.3371986

Petchimuthu, S., Riaz, M., & Kamacı, H. (2022). Correlation coefficient measures and aggregation operators on interval-valued linear diophantine fuzzy sets and their applications. Computational and Applied Mathematics, 41, 409. https://doi.org/10.1007/s40314-022-02077-w

Kannan, J., & Jayakumar, V. (2023). Sustainable method for tender selection using linear diophantine multi-fuzzy soft set. Communications Faculty Of Science University of Ankara Series A1 Mathematics and Statistics, 72(4), 976–991. https://doi.org/10.31801/cfsuasmas.1255830

Kannan, J., Jayakumar, V., Pethaperumal, M., & Shanmugam, N. S. (2024). Linear diophantine multi-fuzzy soft similarity measures: An analysis on alternative-fuel. Journal of Intelligent Fuzzy Systems, 1–13. https://doi.org/10.3233/jifs-219415

Vimala, J., Garg, H., & Jeevitha, K. (2024). Prognostication of Myocardial Infarction Using Lattice Ordered Linear Diophantine Multi-fuzzy Soft Set. International Journal of Fuzzy Systems, 26, 44-59. https://doi.org/10.1007/s40815-023-01574-2

Kannan, J., Jayakumar, V., & Saeid, A. B. (2024). Lattice algebraic structures on ldmfs domains. New Mathematics and Natural Computation, 1–21. https://doi.org/10.1142/s1793005725500218

Jeevitha, K., Vimala, N. J., Banu, K. A., & Sri, S. N. (2024). Enhancing agricultural diagnostics through linear diophantine multi-fuzzy soft matrices with lattice implementation. Contemporary Mathematics, 2593–2618. https://doi.org/10.37256/cm.5320244387

Sri, S. N., Vimala, J., Kausar, N., Ozbilge, E., Özbilge, E., & Pamucar, D. (2024). An mcdm approach on einstein aggregation operators under bipolar linear diophantine fuzzy hypersoft set. Heliyon, 10, e29863. https://doi.org/10.1016/j.heliyon.2024.e29863

Pandipriya, A. R., Vimala, J., & Begam, S. S. (2018). Lattice ordered interval-valued hesitant fuzzy soft sets in decision making problem. International Journal of Engineering Technology, 7(1.3), 52–55. https://doi.org/10.14419/ijet.v7i1.3.9226

Vimala, J., Mahalakshmi, P., Rahman, A. U., & Saeed, M. (2023). A customized TOPSIS method to rank the best airlines to fly during COVID-19 pandemic with q-rung orthopair multi-fuzzy soft information. Soft Computing, 27(20), 14571–14584. https://doi.org/10.1007/s00500-023-08976-2

Pethaperumal, M., Jeyakumar, V., Kannan, J., & Banu, A. (2023). An algebraic analysis on exploring q-rung orthopair multi-fuzzy sets. Journal of Fuzzy Extension and Applications, 4(3), 235–245. https://doi.org/10.22105/jfea.2023.408513.1302

Keshavarz-Ghorabaee, M., Zavadskas, E., Turskis, Z., & Antuchevičienė, J. (2016). A new combinative distance-based assessment (codas) method for multi-criteria decision-making. Economic computation and economic cybernetics studies and research / Academy of Economic Studies, 50(3), 25–44.

Ghorabaee, M. K., Amiri, M., Zavadskas, E. K., Hooshmand, R., & Antuchevičienė, J. (2017). Fuzzy extension of the codas method for multi-criteria market segment evaluation. Journal of Business Economics and Management, 18, 1–19. https://doi.org/10.3846/16111699.2016.1278559

Panchal, D., Chatterjee, P., Shukla, R., Choudhury, T., & Tamošaitienė, J. (2017). Integrated fuzzy ahp-codas framework for maintenance decision in urea fertilizer industry. Economic Computation and Economic Cybernetics Studies and Research, 51(3), 179–196.

Badi, I., Abdulshahed, A. M., & Shetwan, A. (2018). A case study of supplier selection for a steel making company in libya by using the combinative distance based assessment (codas) model. Decision Making: Applications in Management and Engineering, 1(1), 1-12. https://doi.org/10.31181/dmame180101b

Badi, I., Ballem, M., & Shetwan, A. (2018). Site selection of desalination plant in libya by using combinative distance-based assessment (codas) method. International Journal for Quality research, 12(3), 609–624. https://doi.org/10.18421/IJQR12.03-04

Bolturk, E. (2018). Pythagorean fuzzy codas and its application to supplier selection in a manufacturing firm. Journal of Enterprise Information Management, 31(4), 550-564. https://doi.org/10.1108/JEIM-01-2018-0020

Bolturk, E., & Kahraman, C. (2018). Interval-valued intuitionistic fuzzy codas method and its application to wave energy facility location selection problem. Journal of Intelligent Fuzzy Systems, 35(4), 4865-4877. https://doi.org/10.3233/JIFS-18979

Peng, X., & Garg, H. (2018). Algorithms for interval-valued fuzzy soft sets in emergency decision making based on wdba and codas with new information measure. Computers Industrial Engineering, 119, 439–452. https://doi.org/10.1016/j.cie.2018.04.001

Mathew, M., & Sahu, S. (2018). Comparison of new multi-criteria decision making methods for material handling equipment selection. Management Science Letters, 8, 139–150. https://doi.org/10.5267/j.msl.2018.1.004

Pamučar, D., Badi, I., Sanja, K., & Obradović, R. A novel approach for the selection of power-generation technology using a linguistic neutrosophic codas method: A case study in libya. Energies, 11(9), 2489. https://doi.org/10.3390/en11092489

Yeni, F. B., & Özçelik, G. (2019). Interval-valued atanassov intuitionistic fuzzy codas method for multi criteria group decision making problems. Group Decision and Negotiation, 28, 433-452. https://doi.org/10.1007/s10726-018-9603-9

Karaşan, A., Boltürk, E., & Kahraman, C. (2019). A novel neutrosophic codas method: Selection among wind energy plant locations. Journal of intelligent & fuzzy systems, 36(2), 1491-1504. https://doi.org/10.3233/JIFS-181255

Maghsoodi, A. I., Rasoulipanah, H., López, L. M., Liao, H., & Zavadskas, E. K. (2020). Integrating interval-valued multi-granular 2-tuple linguistic bwm-codas approach with target-based attributes: Site selection for a construction project. Computers Industrial Engineering, 139, 106147. https://doi.org/10.1016/j.cie.2019.106147

Ijadi Maghsoodi, A., Ijadi Maghsoodi, A., Poursoltan, P., Antucheviciene, J., & Turskis, Z. (2019). Dam construction material selection by implementing the integrated SWARA—CODAS approach with target-based attributes. Archives of Civil and Mechanical Engineering, 19, 1194-1210. https://doi.org/10.1016/j.acme.2019.06.010

Seker, S. (2020). A novel interval-valued intuitionistic trapezoidal fuzzy combinative distancebased assessment (codas) method. Soft Computing, 24, 2287-2300. https://doi.org/10.1007/s00500-019-04059-3

Peng, X., & Ma, X. (2020). Pythagorean fuzzy multi-criteria decision making method based on codas with new score function. Journal of Intelligent & Fuzzy Systems, 38(3), 3307-3318. https://doi.org/10.3233/JIFS-190043

Aydoğmuş, H. Y., Kamber, E., & Kahraman, C. (2021). Erp selection using picture fuzzy codas method. Journal of Intelligent & Fuzzy Systems, 40(6), 11363-11373. https://doi.org/10.3233/JIFS-202564