Ranking Performance of MARCOS Method for Location Selection Problem in the Presence of Conflicting Criteria

Authors

DOI:

https://doi.org/10.31181/dma21202435

Keywords:

Location Selection Problem, Multiple Criteria Decision Making (MCDM), Measurement Alternatives and Ranking According to Compromise Solution (MARCOS), Conflicting Criteria, Sensitivity Analysis

Abstract

The selection of the best location for a facility is generally a complex process especially when considering multiple criteria in the selection process. The costs associated with purchasing the land and related constructions makes the location selection problem a long-term investment decision. Hence, the problem should be analysed carefully with a reliable approach to avoid the consequences that follows awkward decisions. Many multiple criteria decision-making (MCDM) methods are developed recently which made the selection of a suitable MCDM method has become a confusing decision. In this study, measurement alternatives and ranking according to compromise solution (MARCOS) method is used to solve a location selection problem with conflicting criteria. The ranking produced by MARCOS method is analysed by a comparison with other common MCDM methods and a sensitivity analysis. The aim of the comparison to show that the method agreed the choice of the best alternative while the sensitivity analysis is employed to check the robustness and efficiency of this method. The sensitivity analysis includes the sensitivity of weight test and rank reversal (RR) test. The comparison of ranking with different methods showed that MARCOS method has strong ranking correlation with other methods. Moreover, the sensitivity analysis showed the reliability and robustness of MARCOS method as it produced high consistency of ranking through the tests. Thus, this study validates the applicability of MARCOS method to handle the presence of conflicting criteria in location selection problems.

Downloads

Download data is not yet available.

References

Baker, D., Bridges, D., Hunter, R., Johnson, G., Krupa, J., Murphy, J., & Sorenson, K. (2001). Guidebook to decision-making methods (Vol. 45). Westinghouse Savannah River Company Aiken, SC, USA.

Belton, V., & Stewart, T. (2010). Problem structuring and multiple criteria decision analysis. Trends in Multiple Criteria Decision Analysis, 209–239. https://doi.org/10.1007/978-1-4419-5904-1_8

Nemhauser, G. L., Kan, A. R., & Todd, M. J. (1989). Handbooks in operations research and management science (Vol. 1). Amsterdam: North-Holland.

Hwang, C. L., & Yoon, K. (2012). Multiple attribute decision making: methods and applications a state-of-the-art survey (Vol. 186). Springer Science & Business Media. https://doi.org/10.4135/9781412985161

Fülöp, J. (2005). Introduction to decision making methods. In BDEI-3 workshop, Washington (pp. 1-15).

Opricovic, S., & Tzeng, G. H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European journal of operational research, 156(2), 445-455. https://doi.org/10.1016/S0377-2217(03)00020-1

Gao, C., Li, S., Wang, J., Li, L., & Lin, P. (2018). The risk assessment of tunnels based on grey correlation and entropy weight method. Geotechnical and Geological Engineering, 36, 1621–1631. https://doi.org/10.1007/s10706-017-0415-5

Li, X., Wang, K., Liu, L., Xin, J., Yang, H., & Gao, C. (2011). Application of the entropy weight and TOPSIS method in safety evaluation of coal mines. Procedia Engineering, 26, 2085–2091. https://doi.org/10.1016/j.proeng.2011.11.2410

Tang, H., Shi, Y., & Dong, P. (2019). Public blockchain evaluation using entropy and TOPSIS. Expert Systems with Applications, 117, 204–210. https://doi.org/10.1016/j.eswa.2018.09.048

Huang, W., Shuai, B., Sun, Y., Wang, Y., & Antwi, E. (2018). Using entropy-TOPSIS method to evaluate urban rail transit system operation performance: The China case. Transportation Research Part A: Policy and Practice, 111, 292–303. https://doi.org/10.1016/j.tra.2018.03.025

El-Araby, A. M., Sabry, I., & El-Assal, A. (2021, October). Multi-criteria decision making approaches for facilities planning problem. In 2021 3rd Novel Intelligent and Leading Emerging Sciences Conference (NILES) (pp. 47-50). IEEE. https://doi.org/10.1109/NILES53778.2021.9600538

El-Araby, A. (2023). The utilization of MARCOS method for different engineering applications: a comparative study. International journal of research in industrial engineering, 12(2), 155-164. https://doi.org/10.22105/riej.2023.395104.1379

Saaty, T. L. (1988). What is the analytic hierarchy process?. In Mathematical models for decision support (pp. 109-121). Springer. https://doi.org/10.1007/978-3-642-83555-1_5

Hwang, C. L., & Yoon, K. (1981). Methods for multiple attribute decision making. In Multiple attribute decision making (pp. 58–191). Springer. https://doi.org/10.1007/978-3-642-48318-9_3

Kuo, Y., Yang, T., & Huang, G. W. (2008). The use of grey relational analysis in solving multiple attribute decision-making problems. Computers & Industrial Engineering, 55(1), 80–93. https://doi.org/10.1016/j.cie.2007.12.002

Fishburn, P. C. (1967). Additive utilities with incomplete product sets: Application to priorities and assignments. Operations Research, 15(3), 537–542. https://doi.org/10.1287/opre.15.3.537

Behzadian, M., Kazemzadeh, R. B., Albadvi, A., & Aghdasi, M. (2010). PROMETHEE: A comprehensive literature review on methodologies and applications. European Journal of Operational Research, 200(1), 198–215. https://doi.org/10.1016/j.ejor.2009.01.021

Zavadskas, E. K., Kaklauskas, A., Peldschus, F., & Turskis, Z. (2007). Multi-attribute assessment of road design solutions by using the COPRAS method. The Baltic Journal of Road and Bridge Engineering, 2(4), 195–203.

Keshavarz Ghorabaee, M., Zavadskas, E. K., Olfat, L., & Turskis, Z. (2015). Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (EDAS). Informatica, 26(3), 435–451. https://doi.org/10.15388/Informatica.2015.57

Keshavarz Ghorabaee, M., Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2016). A new combinative distance-based assessment (CODAS) method for multi-criteria decision-making. Economic Computation & Economic Cybernetics Studies & Research, 50(3), 25-44.

Yazdani, M., Zarate, P., Kazimieras Zavadskas, E., & Turskis, Z. (2019). A combined compromise solution (CoCoSo) method for multi-criteria decision-making problems. Management decision, 57(9), 2501-2519. https://doi.org/10.1108/MD-05-2017-0458

Stević, Ž., Pamučar, D., Puška, A., & Chatterjee, P. (2020). Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to COmpromise solution (MARCOS). Computers & Industrial Engineering, 140, 106231. https://doi.org/10.1016/j.cie.2019.106231

Suman, M. N. H., MD Sarfaraj, N., Chyon, F. A., & Fahim, M. R. I. (2021). Facility location selection for the furniture industry of Bangladesh: Comparative AHP and FAHP analysis. International Journal of Engineering Business Management, 13, 18479790211030852. https://doi.org/10.1177/18479790211030851

Ortega, J., Tóth, J., Moslem, S., Péter, T., & Duleba, S. (2020). An Integrated Approach of Analytic Hierarchy Process and Triangular Fuzzy Sets for Analyzing the Park-and-Ride Facility Location Problem. Symmetry, 12(8), 1225. https://doi.org/10.3390/sym12081225

Parhizgarsharif, A., Lork, A., & Telvari, A. (2019). A hybrid approach based on the bwm-vikor and gra for ranking facility location in construction site layout for mehr project in tehran. Decision Science Letters, 8(3), 233–248. https://doi.org/10.5267/j.dsl.2019.3.001

Alkafaas, S. S., Fattouh, M., Masoud, R., & Nada, O. (2020). Intuitionistic Fuzzy VIKOR Method for Facility Location Selection Problem. IN-TERNATIONAL JOURNAL OF ENGINEERING RESEARCH & TECHNOLOGY (IJERT), 9(08), 719-724.

Wang, C.-N., Nguyen, V. T., Thai, H. T. N., & Duong, D. H. (2018). Multi-criteria decision making (MCDM) approaches for solar power plant location selection in Viet Nam. Energies, 11(6), 1504. https://doi.org/10.3390/en11061504

Hossein, S., Alireza, F., & Mohammad, R. F. (2012). Fuzzy multi-criteria decision making method for facility location selection. African Journal of Business Management, 6(1), 206–212.

Chauhan, A., & Singh, A. (2016). A hybrid multi-criteria decision making method approach for selecting a sustainable location of healthcare waste disposal facility. Journal of Cleaner Production, 139, 1001–1010. https://doi.org/10.1016/j.jclepro.2016.08.098

Miç, P., & & Antmen, Z. F. (2019). A healthcare facility location selection problem with fuzzy TOPSIS method for a regional hospital. Avrupa Bilim ve Teknoloji Dergisi, 16, 750–757. https://doi.org/10.31590/ejosat.584217

Ghorui, N., Ghosh, A., Algehyne, E. A., Mondal, S. P., & Saha, A. K. (2020). AHP-TOPSIS inspired shopping mall site selection problem with fuzzy data. Mathematics, 8(8), 1380. https://doi.org/10.3390/math8081380

Ulutaş, A., Karakuş, C. B., & Topal, A. (2020). Location selection for logistics center with fuzzy SWARA and CoCoSo methods. Journal of Intelligent & Fuzzy Systems, 38(4), 4693–4709. https://doi.org/10.3233/JIFS-191400

Hashemkhani Zolfani, S., Bazrafshan, R., Ecer, F., & Karamaşa, Ç. (2022). The suitability-feasibility-acceptability strategy integrated with Bayesian BWM-MARCOS methods to determine the optimal lithium battery plant located in South America. Mathematics, 10(14), 2401. https://doi.org/10.3390/math10142401

Toslak, M., Ulutaş, A., Ürea, S., & Stević, Ž. (2023). Selection of peanut butter machine by the integrated PSI-SV-MARCOS method. International Journal of Knowledge-Based and Intelligent Engineering Systems, 27(1), 73–86. https://doi.org/10.3233/KES-230044

Huskanović, E., Stević, Ž., & Simić, S. (2023). Objective-subjective CRITIC-MARCOS model for selection forklift in internal transport technology processes. Mechatron. Intell Transp. Syst, 2(1), 20–31. https://doi.org/10.56578/mits020103

Żak, J., & Węgliński, S. (2014). The selection of the logistics center location based on MCDM/A methodology. Transportation Research Procedia, 3, 555–564. https://doi.org/10.1016/j.trpro.2014.10.034

El-Araby, A., Sabry, I., & El-Assal, A. (2022). A Comparative Study of Using MCDM Methods Integrated with Entropy Weight Method for Evaluating Facility Location Problem. Operational Research in Engineering Sciences: Theory and Applications, 5(1), 121–138. https://doi.org/10.31181/oresta250322151a

Sałabun, W., & Urbaniak, K. (2020). A new coefficient of rankings similarity in decision-making problems. In Computational Science–ICCS 2020: 20th International Conference, Amsterdam, The Netherlands, June 3–5, 2020, Proceedings, Part II 20 (pp. 632-645). Springer International Publishing.. https://doi.org/10.1007/978-3-030-50417-5_47

Published

2024-04-06

How to Cite

El-Araby, A., Sabry, I., & El-Assal, A. (2024). Ranking Performance of MARCOS Method for Location Selection Problem in the Presence of Conflicting Criteria. Decision Making Advances, 2(1), 148–162. https://doi.org/10.31181/dma21202435