MAKING MORE INFORMED DECISIONS IN MULTI-CRITERIA PROBLEMS UNDER UNCERTAIN CONDITIONS OF CRITERIA WEIGHTS: DRONE SELECTION STUDY CASE

Jakub Więckowski, Wojciech Sałabun

DOI Number
10.22190/FUME240930019W
First page
Last page

Abstract


The growing demand for robust Decision Support Systems (DSS) highlights the need for methods that enhance decision-making under uncertainty, particularly when criteria weights in multi-criteria evaluations are unknown. This study presents a novel approach for addressing Multi-Criteria Decision-Making (MCDM) problems where precise criteria weights are uncertain, focusing on drone selection for challenging, remote locations. Using the MultiAttributive Ideal-Real Comparative Analysis (MAIRCA) method, the research explores a range of criteria weight scenarios with various distributions, enabling a more comprehensive evaluation. A key innovation is the integration of fuzzy ranking techniques to aggregate results from multiple assessments, enhancing the robustness of decision outcomes. This approach overcomes the limitations of traditional ranking aggregation methods, providing a more reliable understanding of the stability and reliability of recommendations. By offering a more adaptive and uncertainty-resilient framework, this study advances multi-criteria decision analysis and improves reliability of recommendations provided by decision support systems in problems in which criteria weights remain unknown. Furthermore, it equips decision-makers with deeper insights into the reliability of recommendations, empowering more confident decision-making in complex, uncertain environments.

Keywords

Drone Selection, Uncertain Weights, Decision Support, Fuzzy Ranking, Decision-Making

Full Text:

PDF

References


Yazdi, M., Khan, F., Abbassi, R., Rusli, R., 2020, Improved DEMATEL methodology for effective safety management decision-making, Safety science, 127, 104705.

Zhai, Z., Martínez, J. F., Beltran, V., Martínez, N. L., 2020, Decision support systems for agriculture 4.0: Survey and challenges, Computers and Electronics in Agriculture, 170, 105256.

Hussain, A., Ullah, K., 2024, An intelligent decision support system for spherical fuzzy sugeno-weber aggregation operators and real-life applications, Spectrum of Mechanical Engineering and Operational Research, 1(1), pp. 177-188.

Yalcin, A. S., Kilic, H. S., Delen, D., 2022, The use of multi-criteria decision-making methods in business analytics: A comprehensive literature review, Technological forecasting and social change, 174, 121193.

Biswas, S., 2020, Measuring performance of healthcare supply chains in India: A comparative analysis of multi-criteria decision making methods, Decision Making: Applications in Management and Engineering, 3(2), pp. 162-189.

Jana, S., Chandra Giri, B., Sarkar, A., Asharaf, S., Jana, C., Pamucar, D., Marinkovic, D., 2024, Selection of brokerage firms for e-services using fuzzy decision making process with AHP and MACROS approaches, Engineering Review, 44 (4 SI), pp. 1 - 21.

Jamwal, A., Agrawal, R., Sharma, M., Kumar, V., 2021, Review on multi-criteria decision analysis in sustainable manufacturing decision making, International Journal of Sustainable Engineering, 14(3), pp. 202-225.

Tadić, D., Lukić, J., Komatina, N., Marinković, D., Pamučar, D., 2025, A Fuzzy Decision-Making Approach to Electric Vehicle Evaluation and Ranking, Tehnički Vjesnik, 32(3), 1066-1075.

Zavadskas, E. K., Pamučar, D., Stević, Ž., Mardani, A., 2020, Multi-criteria decision-making techniques for improvement sustainability engineering processes, Symmetry, 12(6), 986.

Komatina, N., Marinković, D., Tadić, D., Pamučar, D., 2025, Advancing PFMEA decision-making: FRADAR-based prioritization of failure modes using AP, RPN, and multi-attribute assessment in the automotive industry, Tehnički Glasnik/Technical Journal, accepted for publishing.

Hafezalkotob, A., Hafezalkotob, A., Liao, H., Herrera, F., 2019, An overview of MULTIMOORA for multi-criteria decision-making: Theory, developments, applications, and challenges, Information Fusion, 51, pp. 145-177.

Ceballos, B., Lamata, M. T., Pelta, D. A., 2016, A comparative analysis of multi-criteria decision-making methods, Progress in Artificial Intelligence, 5, pp. 315-322.

Sałabun, W., Wątróbski, J., Shekhovtsov, A., 2020, Are mcda methods benchmarkable? a comparative study of topsis, vikor, copras, and promethee ii methods, Symmetry, 12(9), 1549.

Odu, G. O., 2019, Weighting methods for multi-criteria decision making technique, Journal of Applied Sciences and Environmental Management, 23(8), pp. 1449-1457.

Paradowski, B., Shekhovtsov, A., Bączkiewicz, A., Kizielewicz, B., Sałabun, W., 2021, Similarity analysis of methods for objective determination of weights in multi-criteria decision support systems, Symmetry, 13(10), 1874.

Liu, Y., Eckert, C. M., Earl, C., 2020, A review of fuzzy AHP methods for decision-making with subjective judgements, Expert Systems with Applications, 161, 113738.

Kizielewicz, B., Sałabun, W., 2024, SITW method: A new approach to re-identifying multi-criteria weights in complex decision analysis, Spectrum of Mechanical Engineering and Operational Research, 1(1), pp. 215-226.

Şahin, M., 2021, Location selection by multi-criteria decision-making methods based on objective and subjective weightings, Knowledge and Information Systems, 63(8), pp. 1991-2021.

Božanić, D., Epler, I., Puška, A., Biswas, S., Marinković, D., Koprivica, S., 2024, Application of the DIBR II–rough MABAC decision-making model for ranking methods and techniques of lean organization systems management in the process of technical maintenance, Facta Universitatis-Series Mechanical Engineering, 22(1), pp. 101-123.

Nabavi, S. R., Wang, Z., Rangaiah, G. P., 2023, Sensitivity analysis of multi-criteria decision-making methods for engineering applications, Industrial & Engineering Chemistry Research, 62(17), pp. 6707-6722.

Nasr, A., Johansson, J., Larsson Ivanov, O., Björnsson, I., Honfi, D., 2023, Risk-based multi-criteria decision analysis method for considering the effects of climate change on bridges, Structure and Infrastructure Engineering, 19(10), pp. 1445-1458.

Pluchinotta, I., Salvia, G., Zimmermann, N., 2022, The importance of eliciting stakeholders’ system boundary perceptions for problem structuring and decision-making, European Journal of Operational Research, 302(1), pp. 280-293.

Chen, N., Xu, Z., 2015, Hesitant fuzzy ELECTRE II approach: a new way to handle multi-criteria decision making problems, Information Sciences, 292, pp. 175-197.

Wang, L., Yu, Y., Liu, Z., Liu, Z., Liu, X., 2024, An enhanced failure mode and effects analysis risk identification method based on uncertainty and fuzziness, Journal of Engineering Management and Systems Engineering, 3, 116-131.

Hulkower, N. D., Neatrour, J., 2016, Deflecting arrow by aggregating rankings of multiple correlated criteria according to Borda, Journal of Multi‐Criteria Decision Analysis, 23(3-4), pp. 75-86.

Mohammadi, M., Rezaei, J., 2020, Ensemble ranking: Aggregation of rankings produced by different multi-criteria decision-making methods, Omega, 96, 102254.

Azadfallah, M., 2016, A New Aggregation Rule for Ranking Suppliers in Group Decision Mak-

ing under Multiple Criteria, Journal of Supply Chain Management Systems, 5(4).

Ozcalici, M., 2022, Asset allocation with multi-criteria decision making techniques, Decision Making: Applications in Management and Engineering, 5(2), pp. 78-119.

Gigović, L., Pamučar, D., Bajić, Z., Milićević, M., 2016, The combination of expert judgment and GIS-MAIRCA analysis for the selection of sites for ammunition depots, Sustainability, 8(4), 372.

Zolfani, S. H., Ecer, F., Pamučar, D., Raslanas, S., 2020, Neighborhood selection for a newcomer via a novel BWM-based revised MAIRCA integrated model: a case from the Coquimbo-La Serena conurbation, Chile, International Journal of Strategic Property Management, 24(2), pp. 102-118.

Więckowski J., Sałabun W., 2025, Supporting multi-criteria decision-making processes with unknown criteria weights, Engineering Applications of Artificial Intelligence, 140, 109699.

Ozdemir, S., Demirel, N., Zaralı, F., Çelik, T., 2024, Multi-criteria assessment framework for evaluation of Green Deal performance, Environmental Science and Pollution Research, 31(3), pp. 4686-4704.

Tešić, D., Božanić, D., Milić, A., 2023, A multi-criteria decision-making model for pontoon bridge selection: An application of the DIBR II-NWBM-FF MAIRCA approach, Journal of Engineering Management and Systems Engineering, 2(4), 212-223.

Nguyen, H. Q., Nguyen, V. T., Phan, D. P., Tran, Q. H., Vu, N. P., 2022, Multi-criteria decision making in the PMEDM process by using MARCOS, TOPSIS, and MAIRCA methods, Applied sciences, 12(8), 3720.

Rani, P., Chen, S. M., Mishra, A. R., 2023, Multiple attribute decision making based on MAIRCA, standard deviation-based method, and Pythagorean fuzzy sets, Information Sciences, 644, 119274.

Ayan, B., Abacıoğlu, S., Basilio, M. P., 2023, A comprehensive review of the novel weighting methods for multi-criteria decision-making, Information, 14(5), 285.

Arya, V., Kumar, S., 2021, Multi-criteria decision making problem for evaluating ERP system using entropy weighting approach and q-rung orthopair fuzzy TODIM, Granular Computing, 6(4), pp. 977-989.

Bandyopadhyay, S., 2021, Comparison among multi-criteria decision analysis techniques: A novel method, Progress in Artificial Intelligence, 10(2), pp. 195-216.

Keshavarz-Ghorabaee, M., Amiri, M., Zavadskas, E. K., Turskis, Z., Antucheviciene, J., 2021, Determination of objective weights using a new method based on the removal effects of criteria (MEREC), Symmetry, 13(4), 525.

Zavadskas, E. K., Podvezko, V., 2016, Integrated determination of objective criteria weights in MCDM, International Journal of Information Technology & Decision Making, 15(02), pp. 267-283.

Çalık, A., Erdebilli, B., Özdemir, Y. S., 2023, Novel integrated hybrid multi-criteria decision-making approach for logistics performance index, Transportation Research Record, 2677(2), pp. 1392-1400.

Er, A., Özkale, C., Coşkun, S., 2024, Project portfolio selection criteria in the oil & gas industry and a decision support tool based on fuzzy Multimoora, Journal of Project Management, 9(3), pp. 197-212.

Altuntas, S., Dereli, T., Yilmaz, M. K., 2015, Evaluation of excavator technologies: application of data fusion based MULTIMOORA methods, Journal of Civil Engineering and Management, 21(8), pp. 977-997.

Kizielewicz, B., Shekhovtsov, A., Sałabun, W., 2023, pymcdm—The universal library for solving multi-criteria decision-making problems, SoftwareX, 22, 101368.

Paradowski, B., Więckowski, J., Sałabun, W., 2024, PySensMCDA: A novel tool for sensitivity analysis in multi-criteria problems, SoftwareX, 27, 101746.


Refbacks

  • There are currently no refbacks.


ISSN: 0354-2025 (Print)

ISSN: 2335-0164 (Online)

COBISS.SR-ID 98732551

ZDB-ID: 2766459-4