The Selection of Temporary Shelter Areas with Fuzzy TOPSIS Method for the Ankara Province

Abstract

Many people face various types of disasters every year. Within the framework of disaster logistics, temporary shelter areas should be identified before any disaster occurs. The main purpose of this study is to determine the temporary shelter areas in case of a disaster. Fuzzy TOPSIS method was used to fulfill this aim in Ankara due to its being capital and second biggest city of Turkey. In this context, five alternatives were evaluated according to ten criteria determined in accordance with national and international standards by taking expert opinions. Among the five different alternative locations, Etimesgut has been identified as the most suitable temporary shelter area for Ankara. Mamak takes the last place in the ranking. In addition, as a result of the order of alternatives, Yenimahalle was in the second, Çankaya was in the third and Keçiören was in the fourth place in the ranking. Different from the previous studies in the literature, this study focuses on all of the potential disasters. No study has been known on location selection problem of temporary shelter areas after the disaster for Ankara Province.

Keywords

• Multi Criteria Decision Making
• Fuzzy TOPSIS Method
• Disaster Logistics
• Selection of Temporary Shelter Areas

Bulanık TOPSIS Yöntemi ile Ankara İli İçin Olası Afet Sonrası Geçici Barınma Alanlarının Seçimi

Abstract

Her yıl birçok insan çeşitli afet türleri ile karşı karşıya kalmaktadır. Afet lojistiği çerçevesinde, afetzedelerin barınma sorununu çözmek adına geçici barınma alanlarının yerlerinin afet öncesinde belirlenmesi gerekmektedir. Afet sonrası geçici barınma alanlarının seçimi ele alınan problemin ana amacını oluştururken, bu problem gerek Türkiye’nin başkenti, gerekse 2. büyük kenti olmasından ötürü Ankara ili üzerinde Bulanık TOPSIS tekniği ile test edilmektedir. Bu kapsamda, uzman görüşleri alınarak, ulusal ve uluslararası standartlara uygun olarak belirlenen on adet kritere göre beş adet alternatif değerlendirilmiştir. Analiz kapsamında değerlendirilen beş farklı alternatif lokasyon arasında, Ankara ili için Etimesgut en uygun geçici barınma alanı olarak belirlenmiştir. Mamak sıralamada son sırada yer almıştır. Ayrıca, alternatiflerin sıralanması sonucu Yenimahalle ikinci, Çankaya üçüncü ve Keçiören dördüncü sırada çıkmıştır. Bu çalışmada literatürdeki çalışmalardan farklı olarak, bir afet türüne odaklanılmamış; ele alınan potansiyel afetlerin tümüne odaklanılmıştır. Bilinebildiği kadarıyla, bu çalışma ile Ankara ili için afet sonrası geçici barınma alanları ilk kez tespit edilmiştir.

Keywords

• Çok Kriterli Karar Verme
• Bulanık TOPSIS Yöntemi
• Afet Lojistiği
• Geçici Barınma Alanları Seçimi

References

1. Ablanedo-Rosas J.H., Gao H., Alidaee B., Teng W., (2009), Allocation of emergency and recovery centres in Hidalgo, Mexico. International Journal Services Sciences, 2(2), 206-215.
2. AFAD, (2014), T.C. Başbakanlık Afet ve Acil Durum Yönetimi Başkanlığı Türkiye Afet Müdahale Planı, https://www.afad.gov.tr/kurumlar/afad.gov.tr/2419/files/Afet_Mud_Pl_ResmiG_20122013.pdf, [Erişim 24 Nisan 2020].
3. AFAD, (2015), Geçici barınma merkezlerinin kurulması, yönetimi ve işletilmesi hakkında yönerge, https://ailevecalisma.gov.tr/uploads/athgm/uploads/pages/goc-afet-ve-acil-durumlarda-psikososyal-destek/gecici-barinma-merkezlerinin-kurulmasi-yonetimi-ve-isletilmesi-hakkinda-yonerge.pdf, [Erişim 24 Nisan 2020].
4. AFAD, (2016), T.C. Ankara Valiliği İl Afet ve Acil Durum Müdürlüğü “Ankara İl Afet Müdahale Planı”, https://ankara.afad.gov.tr/kurumlar/ankara.afad/4235/files/ANKARA_iL_AFET_MUDAHALE_PLANI.pdf, [Erişim 24 Nisan 2020].
5. Bayram V., Tansel B.Ç., Yaman H., (2015), Compromising systema and user ınterests in Shelter location and evacuation planning, Transportation Research, 72(2015), 146-163.
6. Cakir O., (2008), The grey extent analysis, Kybernetes: The International Journal of Systems & Cybernetics, 37(7), 997-1015.
7. Chang D.Y., (1996), Applications of the extent analysis method on fuzzy AHP, European journal of operational research, 95(3), 649-655.
8. Chen C.T., (2000), Extensions of the TOPSIS for group decision-making under fuzzy environment, Fuzzy sets and systems, 114(1), 1-9.

9. Chen L., (2012), A web-based system for optimizing post disaster temporary housing allocation, MSc Thesis, University of Washington, USA.
10. Chu J.Y., Su Y.P., (2011), Comprehensive evaluation index system in the application for earthquake emergency shelter site, In Advanced Materials Research, 156, 79-83.
11. Dalal J., Mohapatra P.K., Mitra G.C., (2007), Locating cyclone shelters: a case, Disaster Prevention and Management: An International Journal, 16(2), 235-244.
12. Demirci A., Karakuyu M., (2004), Afet yönetiminde coğrafi bilgi teknolojilerinin rolü, Doğu Coğrafya Dergisi, 9(12), 67-100.
13. El-Anwar O., El-Rayes K., Elnashai A., (2009), An automated system for optimizing post-disaster temporary housing allocation, Automation in Construction. 18(7), 983-993.
14. EM-DAT, (2007), EM-DAT; the ODFA/CRED international disaster database, 2006 disasters in numbers, Université Catholique de Louvain, Brussels, Belgium.
15. EM-DAT, (2020), The international disaster database, General Classification, https://www.emdat.be/classification, [Erişim 20 Mayıs 2020].
16. Erkal T., Değerliyurt M., (2009), Türkiye’de afet yönetimi, Doğu Coğrafya Dergisi 14(22), 147-164.
17. Fan C., Zhai G., Zhou S., Zhang H., Qiao P, (2017), Integrated Framework for Emergency Shelter Planning Based on Multihazard Risk Evaluation and Its Application: Case Study in China, Natural Hazards Review, 18(4), 05017003, doi: 10.1061/(ASCE)NH.1527-6996.0000253.
18. Hall G.B., Wang F., Subaryono, (1992), Comparison of Boolean and fuzzy classification methods in land suitability analysis by using geographical information systems, Environment and Planning A, 24(4), 497-516.
19. Hu Z.H., Sheu J.B., Xizo L., (2014), Post-disaster Evacuation and Temporary Resettlement Considering Panic and Panic Spread, Transportation Research, 69, 112-132.
20. Hwang C.L., Yoon K., (1981), Methods for Multiple Attribute Decision Making. In: Multiple Attribute Decision Making. Lecture Notes in Economics and Mathematical Systems, vol 186. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-48318-9_3.
21. Hwang C.L., Lai Y.J., Liu T.Y., (1993), A new approach for multiple objective decision making, Computers & operations research, 20(8), 889-899.
22. IFRC, (2019), What is a Disaster?, https://www.ifrc.org/en/what-we-do/disaster-management/about-disasters/what-is-a-disaster/, [Erişim 20 Mayıs 2020].
23. Junian J. and Azizifar V., (2018), The Evaluation of Temporary Shelter Areas Locations Using Geographic Information System and Analytic Hierarchy Process, Civil Engineering Journal, 4(7), 1678-1688.
24. Kadıoğlu, M., (2008), Modern, Bütünleşik Afet Yönetimin Temel İlkeleri, Afet Zararlarını Azaltmanın Temel İlkeleri’nin İçinde, (Kadıoğlu M., Özdamar E., Ed.), JICA Türkiye Ofisi, Yayın No: 2, Ankara, ss.1-34.
25. Kadıoğlu, M., (2011), Afet yönetimi beklenilmeyeni beklemek, en kötüsünü yönetmek, TC Marmara belediyeler birliği yayını, Yayın No:65, İstanbul, 218ss.
26. Kar B., Hodgson M.E., (2008), A GIS-Based Model to Determine Site Suit- ability of Emergency Evacuation Shelters, Transactions in GIS, 12(2), 227-248.
27. Karaman Z.T., Altay A., (2016), Bütünleşik Afet Yönetimi, İlkem Yayınları, İzmir.
28. Kongsomsaksakul S., Yang C., Chen A., (2005), Shelter Location-allocation Model for Flood Evacuation Planning, Journal of the Eastern Asia Society for Transportation Studies, 6, 4237-4252.
29. Li A.C.Y., Nozick L., Xu N., Davidson R., (2012), Shelter Location and Transportation Planning Under Hurricane Conditions, Transportation Research, 48(4), 715-729.
30. Li L., Jin M., (2010), Sheltering planning and management for natural disasters, http://hurricane.egr.uh.edu/sites/hurricane.egr.uh.edu/ files/files/2010/lingfeng-li.pdf, [Erişim 24 Nisan 2020].
31. Modarres M. and Sadi-Nezhad S., (2001), Ranking fuzzy numbers by preference ratio, Fuzzy sets and Systems, 118(3), 429-436.
32. Omidvar B., Baradaran‐Shoraka M. and Nojavan M., (2013), Temporary site selection and decision‐making methods: a case study of Tehran, Iran, Disasters, 37(3), 536-553.
33. Paksoy T., Pehlivan N.Y., Özceylan E., (2013), Bulanık küme teorisi, Nobel Yayınları, Ankara, 214ss.
34. Pan A., (2010), The applications of maximal covering model in typhoon emergency shelter location problem, 2010 IEEE International Conference on Industrial Engineering and Engineering Management, 7-10 December, Macau, China, ss.1727-1731.
35. Pektaş, T., (2012), İlçe Bazında Afet Lojistiği: Başakşehir Uygulaması, Yüksek Lisans Tezi, Bahçeşehir Üniversitesi, Fen Bilimleri Enstitüsü, İstanbul.
36. Roh S., Pettit S., Harris I., Beresford A., (2015), The pre-positioning of warehouses at regional and local levels for a humanitarian relief organisation, International Journal of Production Economics, 170(2015), 616-628.
37. Shen Y., Wang Q., Yan W., Wang J., (2015), A transportation-location problem model for pedestrian evacuation in chemical industrial parks disasters, Journal of Loss Prevention in the Process Industries, 33(1), 29-38.
38. Soltani A., Ardalan A., Boloorani A.D., Haghdoost A., Hosseinzadeh-Attar M.J., (2015), Criteria for site selection of temporary shelters after earthquakes: a delphi panel, PLoS currents, 7, 1-13.
39. Şentürk E., Erener A., (2017), Determination Of Temporary Shelter Areas In Natural Disasters By Gis A Case Study For Gölcük/Turkey, International Journal of Engineering and Geosciences, 2(3), 84-90.
40. Tarabanis K., Tsionas I., (1999), Using Network Analysis for Emergency Planning in Case of Earthquake, Transactions in GIS, 3(2), 187-197.
41. T.C. Başbakanlık, (1997), Doğal Afetler Genel Raporu, Ankara, 16ss.
42. Thomas A.S., Kopczak L.R., (2005), From logistics to supply chain management: the path forward in the humanitarian sector, Fritz Institute, 15, 1-15.
43. Tong Z., Zhang J., Liu X., (2012), GIS-based design of urban emergency shelter in Songbei Harbin, In Recent advances in computer science and information engineering, Springer, Berlin, Heidelberg, 617-622.
44. Trivedi A., (2018), A multi-criteria decision approach based on DEMATEL to assess determinants of shelter site selection in disaster response, International Journal of Disaster Risk Reduction, 31, 722-728.
45. TÜİK, (2019), Adrese Dayalı Nüfus Kayıt Sistemi Sonuçları, Retrieved from https://biruni.tuik.gov.tr/medas/?kn=95&locale=tr, [Erişim 30 Nisan 2020].
46. UN/ISDR, (2007), United Nations/International Strategy for Disaster Reduction, Geneva, Switzerland, http://www.unisdr.org, [Erişim 31 Ocak 2020].
47. URL-1, (2011), The Sphere Project: Humanitarian Charter and Minimum Standards in Humanitarian Response, http://www.sphereproject.org/handbook/, [Erişim 31 Ocak 2020].
48. Van Wassenhove L.N., (2006), Humanitarian aid logistics: supply chain management in high gear, Journal of the Operational Research Society, 57(5), 475-489.
49. Wang Y.J. and Lee H.S., (2007), Generalizing TOPSIS for fuzzy multiple-criteria group decision-making, Computers & Mathematics with Applications, 53(11), 1762-1772.
50. Wex F., Schryen G., Feuerriegel S., Neumann D., (2014), Emergency Response in Natural Disaster Management: Allocation and Scheduling of Rescue Units, European Journal of Operational Research, 235(3), 697-708.
51. Yiğitcanlar T., Bolposta R., Yankaya U., Kınac O., Baradan B., Bektaş B., (2005), Afet Sonrası Geçici Yerleşim Alanlarının Tasarımında Stratejik Seçim Yaklaşımı, Planlama, 2005(2), 89-100.
52. Yoon K., (1987), A reconciliation among discrete compromise solutions, Journal of the Operational Research Society, 38(3), 277-286.
53. Youssef A.M., Pradhan B., Hassan A.M., (2011), Flash Flood Risk Estimation Along the St. Katherine Road, Southern Sinai, Egypt Using GIS Based Morphometry and Satellite Imagery, Environmental Earth Sciences, 62(3), 611-623.
54. Zadeh L.A., (1965), Fuzzy sets, Information and control, 8(3), 338-353.
55. Zeleny M., (1982), Multiple criteria decision making, McGraw-Hill, New York, 563ss.