POST-EARTHQUAKE RELIEF LOGISTICS CENTER LOCATION SELECTION: A NOVEL HYBRID IT2 F-RANCOM + IT2 F-MOORA APPROACH

Öz

The selection of post-disaster humanitarian logistics centers plays a critical role in ensuring the rapid and effective delivery of aid in affected regions. This study aims to develop and implement the proposed hybrid model that can more effectively model uncertainties in post-earthquake humanitarian logistics center location selection. The province of Hatay, one of the areas most severely affected by the 2023 Kahramanmaraş-centered earthquakes, was selected as the case study area. Six evaluation criteria and five alternative regions were considered. Initially, the fuzzy performance values of the alternatives were calculated using the IT2 F-MOORA method. Subsequently, the final ranking was obtained through reference-normalized values using the IT2 F-RANCOM method. The results indicated that A2 (Northern Hatay Region) was the most suitable alternative with a score of 1.000, followed by A1 (Central Hatay Region) with 0.950 and A3 (Eastern Hatay Region) with 0.732. A sensitivity analysis was conducted by varying the weight of the reference criterion C1 (Disaster Risk) between +15% and +65% in increments of +10%. The analysis showed that the proposed hybrid approach maintained ranking stability. Even under maximum weight variation, A2 remained the most suitable location, and no changes occurred in the ranking of the other alternatives. This indicates that the proposed model is resilient to uncertainties and provides policymakers with a reliable decision support tool for post-disaster logistics planning.

Anahtar Kelimeler

• Disaster Logistics
• Location Selection
• Interval Type-2 Fuzzy MOORA
• IT2 F-RANCOM Method
• MCDM

DEPREM SONRASI YARDIM LOJİSTİK MERKEZİ YERİ SEÇİMİ: YENİ BİR HİBRİT IT2 F-RANCOM + IT2 F-MOORA YAKLAŞIMI

Öz

Deprem sonrası yardım lojistik merkezi seçimi, insani yardımların hızlı ve etkin ulaştırılmasında kritik rol oynar. Bu çalışmanın amacı, bu probleme yönelik belirsizlikleri etkin şekilde modelleyen önerilen hibrit modeli geliştirmek ve uygulamaktır. Çalışma alanı olarak, 2023 Kahramanmaraş merkezli depremlerinden en fazla etkilenen illerden biri olan Hatay ili seçilmiştir. Değerlendirme sürecinde altı kriter ve beş alternatif bölge dikkate alınmıştır. İlk aşamada IT2 F-MOORA yöntemi ile alternatiflerin bulanık performans değerleri hesaplanmış, ardından IT2 F-RANCOM yöntemi ile referans normalize değerler üzerinden nihai sıralama yapılmıştır. Elde edilen sonuçlara göre, A2 (Hatay Kuzey Bölgesi) 1.000’lık skor değeriyle en uygun alternatif olarak belirlenmiştir. Bu alternatifi A1 (Hatay Merkez Bölgesi) 0.950 ve A3 (Hatay Doğu Bölgesi) 0.732 skorlarıyla takip etmektedir. Ayrıca, referans kriter olarak alınan C1 (Afet Riski) kriterindeki ağırlık değerine +%15 - +%65 aralığında +%10 oranlarında yapılan duyarlılık analizi sonucunda, önerilen hibrit yaklaşımının sıralama kararlılığını koruduğu gözlemlenmiştir. En yüksek ağırlık değişiminde dahi A2 alternatifi en uygun lojistik merkezi olarak konumunu sürdürmüş, diğer alternatiflerin sıralamasında herhangi bir değişiklik olmamıştır. Bu durum, önerilen modelin belirsizliklere karşı dayanıklı olduğunu ve politika yapıcılarına afet sonrası lojistik planlamada güvenilir bir karar destek aracı sunacağını göstermektedir.

Anahtar Kelimeler

• Afet Lojistiği
• Yer Seçimi
• Aralık Tip-2 Bulanık MOORA
• RANCOM Yöntemi
• ÇKKV

Kaynakça

1. Aktas Potur, E., Aktas, A., Kabak, M., 2025. A Bibliometric Analysis of Multi-Criteria Decision-Making Techniques in Disaster Management And Transportation İn Emergencies: Towards Sustainable Solutions. Sustainability, 17(6), 2644.
2. Altay, N., Green, W.G., 2006. OR/MS Research in Disaster Operations Management. European Journal of Operational Research, 175(1), 475–493.
3. Balcik, B., Beamon, B. M., 2008. Facility Location in Humanitarian Relief. International Journal of Logistics, 11(2), 101–121.
4. Behl, A., Dutta, P., 2019. Humanitarian supply chain management: A thematic literature review and future directions of research. Annals of Operations Research, 283(1–2), 1001–1044.
5. Brauers, W.K.M., Zavadskas, E.K., 2006. The MOORA Method And its Application to Privatization in a Transition Economy. Control and Cybernetics, 35(2), 445–469.
6. Büyüközkan, G., Çifçi, G., 2012. A Novel Fuzzy Multi-Criteria Decision Framework for Sustainable Supplier Selection. Computers in Industry, 63(8), 729–741.
7. Demir, H., Sezer, M.D., 2022. Çok Kriterli Karar Verme Yöntemleri ile Afet Lojistik Merkezi Yeri Seçimi: Van İli örneği. Uluslararası Afet ve Dirençlilik Dergisi, 5(1), 45–58.
8. Demirtaş, H., Kılınç, H., 2022. Bulanık VIKOR yöntemi ile afet sonrası geçici yerleşim alanlarının belirlenmesi. Mühendislik Bilimleri ve Tasarım Dergisi, 10(3), 746–760.

9. Deniraraslan, P. Ç., 2023. Resim Bulanık (Picture Fuzzy) Küme Tabanlı Çok Kriterli Karar Verme Yaklaşımı ve Uygulamaları. Doktora Tezi. Bartın Üniversitesi, Türkiye.
10. Dikopoulou, Z., Nápoles, G., Papageorgiou, E., Vanhoof, K., 2017. A Modified Fuzzy TOPSIS Method Aggregating Partial Rankings for Companies’ Attractiveness. In The Application of Fuzzy Logic for Managerial Decision Making Processes: Latest Research and Case Studies (pp. 59–71). Cham: Springer International Publishing.
11. Eelagh, M. D., Abbaspour, R. A., 2024. A Location-Allocation Optimization Model for Post-Earthquake Emergency Shelters Using Network-Based Multi-Criteria Decision-Making. Decision Analytics Journal, 10, 100430.
12. Ergün, M., Korucuk, S., Memiş, S., 2020. Sürdürülebilir Afet Lojistiğine Yönelik İdeal Afet Depo Yeri Seçimi: Giresun İli Örneği. Çanakkale Onsekiz Mart Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 6(1), 144–165.
13. Feng, Z., Li, G., Wang, W., Zhang, L., Xiang, W., He, X., Wei, N., 2023. Emergency Logistics Centers Site Selection by Multi-Criteria Decision-Making and GIS. International Journal of Disaster Risk Reduction, 96, 103921.
14. Ghorabaee, M. K., Amiri, M., Zavadskas, E. K., Turskis, Z., Antucheviciene, J., 2017. A New Multi-Criteria Model Based on Interval Type-2 fuzzy Sets and EDAS Method for Supplier Evaluation and Order Allocation with Environmental Considerations. Computers & Industrial Engineering, 112, 156–174.
15. Govindan, K., Khodaverdi, R., Jafarian, A., 2013. A fuzzy Multi Criteria Approach for Measuring Sustainability Performance of A Supplier Based on Triple Bottom Line Approach. Journal of Cleaner Production, 47, 345–354.
16. Hanberry, B. B., 2022. Imposing Consistent Global Definitions of Urban Populations with Gridded Population Density Models: Irreconcilable Differences at The National Scale. Landscape and Urban Planning, 226, 104493.
17. He, M., Shen, J., Wu, X., Luo, J., 2018. Logistics Space: A Literature Review from the Sustainability Perspective. Sustainability, 10(8), 2815.
18. Kabak, M., Kılınç, N., Ülengin, F., 2021. Integrated IT2 F-MOORA Approach for Evaluating Urban Infrastructure Alternatives. Sustainable Cities and Society, 64, 102547.
19. Kabak, Ö., Ervural, B.Ç., Cebi, S., 2021. A Novel IT2 Fuzzy MCDM Approach for Prioritizing Disaster Waste Management Alternatives. Expert Systems with Applications, 165, 113871.
20. Kahraman, C., Cebeci, U., Ruan, D., 2007. Multi-Attribute Comparison of Catering Service Companies Using Fuzzy AHP: The Case of Turkey. International Journal of Production Economics, 87(2), 171–184.
21. Karabasevic, D., et al., 2022. Interval Type-2 Fuzzy MOORA Method for Personnel Selection in Crisis Conditions. Symmetry, 14(9), 1903.
22. Karabasevic, D., Stanujkic, D., Zavadskas, E.K., Chatterjee, P., 2022. Personnel Selection in Crisis Conditions Using Interval-Valued Intuitionistic Fuzzy MOORA Method. Technological and Economic Development of Economy, 28(3), 523–545.
23. Karataş, N., Kaya, M.A., 2022. Deprem Riskinin Kentsel Planlama Sürecine Etkisi: İpsala, Keşan ve Enez ilçeleri (Edirne) Örneği. Journal of Engineering Sciences and Design, 10(2), 654–679.
24. Karnik, N. N., Mendel, J. M., 2001. Centroid of a Type-2 Fuzzy Set. Information Sciences, 132(1–4), 195–220.
25. Kaya, T., Kahraman, C., 2023. A Novel Interval Type-2 Fuzzy Decision Making Approach for Energy Investment Evaluation. Energy Reports, 9, 268–284.
26. Kaya, T., Kahraman, C., 2023. Renewable Energy Site Selection with Interval Type-2 Fuzzy AHP and MOORA Methods. Energy Reports, 9, 212–226.
27. Khan, M.A., Rehman, A., Abbas, S., 2024. Integrated Fuzzy-BWM and IT2F-TOPSIS Approach for Flood Relief Logistics Hub Selection. International Journal of Disaster Risk Reduction, 97, 104103.
28. Khodadadi, S., Tasooji, T. K., Shariat-Mohayman, A., Kalantari, N., 2025. A Multi-Objective Simultaneous Routing, Facility Location and Allocation Model for Earthquake Emergency Logistics. arXiv preprint arXiv:2503.22487.
29. Kılıç, A., Yücel, C., 2020. Afet Sonrası Lojistik Merkez Yeri Seçimi: Bulanık AHP ve VIKOR Yaklaşımları. Dicle Üniversitesi Mühendislik Fakültesi Mühendislik Dergisi, 11(2), 623–636.
30. Lisso, L., Lindsay, J. B., Berg, A., 2024. Evaluating The Topographic Factors for Land Suitability Mapping Of Specialty Crops in Southern Ontario. Agronomy, 14(2), 319.
31. Mendel, J. M., 2007. Advances in Type-2 Fuzzy Sets And Systems. Information Sciences, 177(1), 84–110.
32. Mendel, J.M., 2017. Uncertain Rule-Based Fuzzy Systems with Interval Type-2 Fuzzy Sets (2nd ed.). Springer.
33. Özdemir, S., Yılmaz, A., 2021. Afet Lojistik Merkezlerinin Yeri Seçimi İçin Entegre Çok Kriterli Karar Verme Yaklaşımı. Gazi University Journal of Science Part A: Engineering and Innovation, 8(2), 155–170.
34. Öztürk, M., 2025. A Hybrid Approach for Battery Selection Based on Green Criteria In Electric Vehicles: DEMATEL-QFD-interval Type-2 fuzzy VIKOR. Sustainability, 17(14), 6277.
35. Öztürk, M., 2026. Equipment Supplier Selection for Sustainable Hydrogen Production: A Group Decision-Making Supported Spherical Fuzzy TOPSIS Approach. Sustainability, 18(4), 1737.
36. Rai, H. B., Kang, S., Sakai, T., Tejada, C., Yuan, Q. J., Conway, A., Dablanc, L., 2022. ‘Proximity Logistics’: Characterizing the Development of Logistics Facilities in Dense, Mixed-Use Urban Areas Around the World. Transportation Research Part A: Policy and Practice, 166, 41–61.
37. ReliefWeb., 2024. 2024 Disasters Numbers. Retrieved October 5, 2025, from https://reliefweb.int/report/world/2024-disasters-numbers
38. Ranjbar, S., Zandieh, M., Esfahani, M.M.S., 2023. Post-Disaster Supply Chain Resilience Enhancement Using Fuzzy DEMATEL–MARCOS Approach. Journal of Humanitarian Logistics and Supply Chain Management, 13(1), 65–89.
39. Sakai, T., Beziat, A., Heitz, A., 2020. Location Factors for Logistics Facilities: Location Choice Modeling Considering Activity Categories. Journal of Transport Geography, 85, 102710.
40. Scholz, S., Ngoli, B., Flessa, S., 2015. Rapid Assessment of İnfrastructure of Primary Health Care Facilities – A Relevant İnstrument For Health Care Systems Management. BMC Health Services Research, 15(1), 183.
41. Singh, R., Pathak, V. K., Kumar, R., Dikshit, M., Aherwar, A., Singh, V., Singh, T., 2024. A Historical Review and Analysis on MOORA and its Fuzzy Extensions for Different Applications. Heliyon, 10(3).
42. Sodhi, B., Prabhakar, T. V., 2012. A Simplified Description of Fuzzy TOPSIS. arXiv preprint arXiv:1205.5098.
43. Stanujkic, D., Magdalinovic, N., Stojanovic, S., Jovanovic, R., 2012. Extension of Ratio System Part of MOORA Method for Solving Decision-Making Problems with Interval Data. Informatica, 23(1), 141–154.
44. Stević, Ž., et al., 2020. The MARCOS Method for Decision-Making in Complex and Uncertain Environments: A Novel Approach. Symmetry, 12(3), 455.
45. Taguta, C., Dirwai, T. L., Senzanje, A., Sikka, A., Mabhaudhi, T., 2022. Sustainable İrrigation Technologies: A Water-Energy-Food (WEF) Nexus Perspective Towards Achieving More Crop Per Drop Per Joule Per Hectare. Environmental Research Letters, 17(7), 073003.
46. TMMOB. (2023, Ekim 6). TMMOB 6 Şubat Depremleri 8. Ay Değerlendirme Raporu Yayımlandı. https://www.tmmob.org.tr/icerik/tmmob-6-subat-depremleri-8-ay-degerlendirme-raporu-yayimlandi
47. U.S. Department of Defense, 2014. UFC 4-440-01: Warehouses and Storage Facilities. Unified Facilities Criteria. Retrieved from https://www.wbdg.org/FFC/DOD/UFC/ARCHIVES/ufc_4_440_01_2014.pdf
48. UNDRR, 2025. National disaster risk assessment: A Guide for National Practitioners. United Nations Office for Disaster Risk Reduction. Retrieved from https://www.undrr.org/publication/national-disaster-risk-assessment-guide-national-practitioners
49. Vaillancourt, A., Haavisto, I., 2016. Country Logistics Performance and Disaster İmpact. Disasters, 40(2), 262-283.
50. Wang, H., Luo, P., Wu, Y., 2023. Research on the Location Decision-Making Method of Emergency Medical Facilities Based on WSR. Scientific Reports, 13(1), 18011.
51. Więckowski, J., Kizielewicz, B., Shekhovtsov, A., Sałabun, W., 2023. RANCOM: A Novel Approach to İdentifying Criteria Relevance Based on Inaccuracy Expert Judgments. Engineering Applications of Artificial Intelligence, 122, 106114.
52. Xu, F., Ma, Y., Liu, C., Ji, Y., 2024. Emergency Logistics Facilities Location Dual-Objective Modeling in Uncertain Environments. Sustainability, 16(4), 1361.
53. Zadeh, L.A., 1975. The Concept of a Linguistic Variable and its Application to Approximate Reasoning—III. Information Sciences, 9(1), 43-80.
54. Zeng, S., Zhang, Y., 2007. A Method of Fuzzy Comprehensive Evaluation Based on Interval Type-2 Fuzzy Sets. Journal of Systems Engineering and Electronics, 18(1), 187–191.
55. Zhou, Y., Zhang, L., 2023. Earthquake Emergency Logistics Center Location Selection Using Interval Type-2 Fuzzy AHP and MOORA. Expert Systems with Applications, 213, 119153.
56. Ziadat, F. M., 2007. Land Suitability Classification Using Different Sources of İnformation: Soil Maps and Predicted Soil Attributes in Jordan. Geoderma, 140(1–2), 73–80.