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Journals / Endüstri Mühendisliği / 2026 / Cilt: 35 Sayı: 1

MAXIMAL COVERING METHOD IN DETERMINING DISTRIBUTION CENTERS IN DISASTER LOGISTICS

AFET LOJİSTİĞİNDE DAĞITIM MERKEZLERİNİN BELİRLENMESİNDE EN BÜYÜK KAPSAMA YÖNTEMİ

Murat Koç(Kızılay Teknoloji A. Ş.)0000-0002-7638-7526
Hüseyin Ali Sarıkaya(Mudanya Üniversitei)0000-0001-5072-5067
Pages
22–60
Publication Date
2024-04-30
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Six different scenarios have been created for the developed model, optimal solutions have been obtained for each scenario using ArcGIS Route Solver software and the solutions have been analyzed by changing the problem parameters.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Efforts to determine the location of a physical object, known as the location problem, are not new.
📊
Key Findings & Data:Facility location decisions of emergency service centres such as schools, hospitals, fire brigades, disaster response points have an important place in the strategic planning of the activities of public and private organisations.
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Conclusion & Impact:Six different scenarios have been created for the developed model, optimal solutions have been obtained for each scenario using ArcGIS Route Solver software and the solutions have been analyzed by changing the problem parameters.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Afet Yönetimi · Yer Seçimi Problemleri · Enbüyük Kapsama Problemi

Abstract

Efforts to determine the location of a physical object, known as the location problem, are not new. For centuries, people have solved location problems and found various methods by formulating problems or somehow trying to optimally place objects and service centres in relation to other objects and service centres. Facility location decisions of emergency service centres such as schools, hospitals, fire brigades, disaster response points have an important place in the strategic planning of the activities of public and private organisations. In this study, it is aimed to determine the places where the necessary materials will be stored in order to meet the needs of disaster victims such as food, shelter, clothing and first aid in case of a disaster that may occur in our country. Within the framework of this purpose, the study has been carried out by taking into consideration the Turkish Red Crescent (TRC) disaster warehouses, disaster map and the disasters experienced in recent years. In Izmir Regional Disaster Management Centre (RDMC) selected as an example, first the coverage distances of each Red Crescent RDMC according to the criteria of response to the disasters, then the candidate points representing the potential warehouse locations and the demand points showing the disasters that the Red Crescent RDMC should respond to have been determined by using the Geographical Information System (GIS). While determining the most appropriate locations of the warehouses to be established, the Maximum Covering Location Problem has been selected from the facility location problem types. Six different scenarios have been created for the developed model, optimal solutions have been obtained for each scenario using ArcGIS Route Solver software and the solutions have been analyzed by changing the problem parameters.

Özet

Yer seçimi problemi olarak bilinen fiziksel bir nesnenin yerini belirleme çabaları yeni değildir. Yüzyıllar boyunca insanlar yer seçimi problemlerini çözmüşler ve problemleri formüle ederek veya bir şekilde nesneleri ve hizmet merkezlerini diğer nesne ve hizmet merkezlerine göre en uygun şekilde yerleştirmeye çalışarak çeşitli yöntemler bulmuşlardır. Okul, hastane, itfaiye, afet müdahale noktaları gibi acil hizmet merkezlerinin tesis yerlerinin belirlenmesi kararları, kamu ve özel kuruluşların faaliyetlerinin stratejik planlanmasında önemli bir yere sahiptir. Bu çalışmada ülkemizde meydana gelebilecek afet durumunda afetzedelerin gıda, barınma, giyecek ve ilk yardım gibi gereksinimlerin karşılanabilmesi için gerekli olan malzemelerin depolanacağı yerlerin belirlenmesi amaçlanmıştır. Bu amaç çerçevesinde Türk Kızılay afet depoları, afet haritası ve son yıllarda yaşanan afetler göz önünde bulundurularak çalışma yapılmıştır. Örnek olarak seçilen İzmir Bölge Afet Yönetim Merkezi (BAYM)’nde ilk önce her Kızılay BAYM’nin afetlere müdahale kriterine göre kapsama mesafeleri, daha sonra potansiyel depo yerlerini temsilen aday noktaları ve Kızılay BAYM’nin müdahale etmesi gereken afetleri gösteren talep noktaları Coğrafi Bilgi Sistemi (GIS)nden faydalanılarak belirlenmiştir. Kurulacak depoların en uygun yerleri belirlenirken yer seçimi problem türlerinden Enbüyük Kapsama Yer Seçimi Problemi seçilmiştir. Geliştirilen model için altı ayrı senaryo oluşturulmuş, ArcGIS Route Solver yazılımı kullanılarak optimal çözümler elde edilmiş ve problem parametreleri değiştirilerek bu çözümler analiz edilmiştir.

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Cite This Article

Koç, M., Sarıkaya, H. A. (2024). MAXIMAL COVERING METHOD IN DETERMINING DISTRIBUTION CENTERS IN DISASTER LOGISTICS. Endüstri Mühendisliği, Cilt: 35 Sayı: 1, 22–60. https://doi.org/10.46465/endustrimuhendisligi.1357156

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References (40)

  1. Ağdaş, M., Bali, Ö. & Ballı, H. (2014). Afet lojistiği kapsamında dağıtım merkezi için yer seçimi: SMAA-2 tekniği ile bir uygulama. Beykoz Akademi Dergisi, 2(1), 75-94. issue/52159/682113.
  2. Alizadeh, R. & Nishi, T. (2020). Hybrid Set Covering and Dynamic Modular Covering Location Problem: Application to an Emergency Humanitarian Logistics Problem. Applied Sciences, 10(20), 7110. Doi: https://doi.org/10.3390/app10207110
  3. Alizadeh, R., Nishi, T., Bagherinejad, J. & Bashiri, M. (2021). Multi-period maximal covering location problem with capacitated facilities and modules for natural disaster relief services. Applied Sciences, 11, 397. Doi: https://doi.org/10.3390/app11010397
  4. Balcik, B. & Beamon, B. M. (2008). Facility location in humanitarian relief, International Journal of Logistics Research and Applications, 11(2), 101-121. Doi: https://doi.org/10.1080/13675560701561789
  5. Batta, R. & Mannur, N. R. (1990). Covering-Location Models for Emergency Situations That Require Multiple Response Units, Management Science, XXXVI, 16-23. Doi: https://doi.org/10.1287/%20mnsc.36.1.16
  6. Blanquero, R., Carrizosa, E. & G.-Tóth, B. (2016). Maximal Covering Location Problems on networks with regional demand, Omega, 64, 77-85. Doi: https://doi.org/10.1016/j.omega.2015.11.004
  7. Church, R. L. & ReVelle, C. (1974). Maximal covering location problem. 32 (1), 101-118. Papers of the Regional Science Association. Doi: https://doi.org/10.1111/j.1435-5597.1974.%20tb00902.x
  8. Coco, A. A., Santos, A. C. & Noronha, T. F. (2018). Formulation and algorithms for the robust maximal covering location problem. Electronic Notes Discrete Math., 64, 145-154.Doi: https://doi.org/10.1016/j.endm.2018.01.016
  9. Cordeau, J. F., Furini, F. & Ljubić, I. (2019). Benders decomposition for very large scale partial set covering and maximal covering location problems. European Journal of Operational Research, 275, 3, 882-896. Doi: https://doi.org/10.1016/j.ejor.2018.12.021
  10. Curtin, K. M., Hayslett-McCall, K. & Qiu, F. (2010). Determining Optimal Police Patrol Areas with Maximal Covering and Backup Covering Location Models. Netw Spat Econ, 10, 125–145. Doi: https://doi.org/10.1007/s11067-007-9035-6
  11. Çavdur, F. & Sebatlı, A. (2019). A decision support tool for allocating temporary-disaster-response facilities. Decision Support Systems, 127, 113145. Doi: https://doi.org/10.1016/j.dss.2019.113145
  12. Daskin, M. S., & Stern, E. H. (1981). A hierarchical objective set covering model for emergency medical service vehicle deployment. Transportation Science, 15(2), 137-152. Doi: https://doi.org/10.1287/trsc.15.2.137
  13. Davari, S., Zarandi, M. H. F., & Hemmati, A. (2011). Maximal covering location problem (MCLP) with fuzzy travel times, Expert Systems with Applications, 38(12), 14535-14541.Doi: https://doi.org/10.1016/j.eswa.2011.05.031
  14. Densham, P. J., & Rushton, G. (1992). A more efficient heuristic for solving large p-median problems. Papers in Regional Science: The Journal of The RSAI, 72, 307-329. Doi: https://doi.org/10.1111/ j.1435-5597.1992.tb01849.x.
  15. Doungpan, S., Moryadee, S., U-tapao, C. & Laokhongthavorn, Z. (2018). Analysis of three emergency medical location models: A case study of Thailand. Proceedings of International Conference on System Science and Engineering (ICSSE), 1-6, New Taipei, Taiwan. Doi: https://doi.org/10.1109/ICSSE.2018.8520208
  16. Drakulić D., Takači A. & Marić M. (2016). New model of maximal covering location problem with fuzzy conditions, Computing and Informatics, 35 (2016), 635-652. Retrieved from https://www.scopus.com/record/ display.uri?eid=2-s2.0-84989184455&origin=inward&txGid=98ebe7 fd8be6e492182a6b1533c23a2b
  17. Drezner, Z., & Wesolowsky, G.O. (1995). Location on a one-way rectilinear grid. Journal of the Operational Research Society, 46(6), 735-746. Doi: https://doi.org/10.1057/jors.1995.103
  18. Durak, İ. & Yıldız, M. S. (2015). P-Medyan Tesis Yeri Seçim Problemi: Bir Uygulama. Uluslararası Alanya İşletme Fakültesi Dergisi, Antalya, Türkiye. Ergin, C. (2016). Afet lojistiğinde depo yeri seçim probleminin optimizasyon ve kümeleme teknikleri ile çözülmesi (Yüksek lisans tezi). Sakarya Üniversitesi, Fen Bilimleri Enstitüsü, Sakarya, Türkiye. Retrieved from https://acikerisim.sakarya.edu.tr/bitstream/handle/20.500.12619/79732/T06720.pdf?sequence=1&isAllowed=y
  19. Garey, M. R., & Johnson, D. S. (1979). Computers and intractability: A guide to the theory of NP completeness, New York USA: Freeman and Company. https://www.amazon.com/Computers-Intractability-NP-Completeness-Mathematical-Sciences/dp/0716710455
  20. Gencer, C. & Açıkgöz, A. (2006). Türk Silahlı Kuvvetleri arama kurtarma timlerinin yerleşiminin yeniden düzenlenmesi. Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, 21(1), 87-105. /issue/6667/88813
  21. Hakimi, S. L. (1964). Optimum Locations of Switching Centers and the Absolute Centers and Medians of a Graph. Operations Research, 12(3), 450-459. Doi: https://doi.org/10.1287/opre.12.3.450
  22. Hashtarkhani, S., A. Matthews, S., Yin, P., Mohammadi, A., MohammadEbrahimi, S., Tara, M., & Kiani, B. (2023). Where to place emergency ambulance vehicles: use of a capacitated maximum covering location model with real call data. Geospatial Health, 18(2). Doi: https://doi.org/10.4081/gh.2023.1198
  23. Karabay, S., Köse, E. & Kabak, M. (2014). Stokastik çok kriterli kabul edilebilirlik analizi ile bir kamu kurumu için tesis yeri seçimi. Ege Akademik Bakış, 14(3), 361-369 Kurban, Ö. & Can, T. (2016). Acil istihbarat, gözetleme ve keşif ihtiyaçları için mini insansız hava araçlarının yer kontrol istasyonlarının seçimi. Öneri Dergisi, 12(45), 35-59. Owen, S. H. & Daskin, M. S. (1998). Strategic Facility Location: A Review, European Journal of Operational Research, CXI, 423-447. Doi: https://doi.org/10.1016/S0377-2217(98)00186-6
  24. Özkan, B., Mete, S., Çelik, E. & Özceylan, E. (2019). GIS-based maximum covering location model in times of disasters: The case of Tunceli. Beykoz Akademi Dergisi, 100-111. Doi: https://doi.org/10.14514/byk.m. 26515393.2019.sp/100-111
  25. Polat, G. E. (2021). Distribution Centre Location Selection for Disaster Logistics with Integrated Goal Programming-AHP based TOPSIS Method at the City Level. Afet ve Risk Dergisi, 5(1), 282-296. Doi: https://doi.org/10.35341/afet.1071343
  26. Rath, S. & Gutjahr, W. J. (2014). A math-heuristic for the warehouse location–routing problem in disaster relief, Computers & Operations Research, 42, 25-39. Doi: https://doi.org/10.1016/j.cor.2011.07.016
  27. Rawls, C. G. & Turnquist, M. A. (2011). Pre-positioning planning for emergency response with service quality constraints. OR Spectrum, 33 (3): 481–98. Doi: https://doi.org/10.1007/s00291-011-0248-1
  28. ReVelle, C.S., Williams, J.C. & Boland, J.J. (2002). Counterpart Models in Facility Location Science and Reserve Selection Science. Environmental Modeling & Assessment 7, 71–80. Doi: https://doi.org/10.1023/A:1015641514293
  29. ReVelle, C. S. & Eiselt, H. A. (2005). Location analysis: A synthesis and survey, European Journal of Operational Research, 165, No. 1, 1–19. Doi: https://doi.org/10.1016/j.ejor.2003.11.032
  30. Santoso, S. & Heryanto, R. M. (2022). Development of the capacitated maximal covering location problem (CMCLP) model in determining the location and type of distribution center. Doi: https://doi.org/10.31315/opsi.v15i1.6431
  31. Sarıkaya, H. A., Aygüneş, H. & Kılıç. A. (2020). Jandarma karakollarının yer seçiminin enbüyük kapsama metodu ile belirlenmesi. Endüstri Mühendisliği, 31 (1), 28-47. endustrimuhendisligi/ issue/53786/603442
  32. Serra, D. & Revelle, C. (1995). “Competitive location in discrete space”, Facility Location A Survey of Applications and Methods, Springer, 978-0387945453, New York, 1995.Springer Series in Operations Research, New York, 367-386. Retrieved from https://www.amazon.com.tr/Facility-Location-Applications-Operations-Engineering/dp/0387945458
  33. Weber, A. (1909). Über den Standort der Industrien, Erster Teil: Reine Theorie des Standortes, The University of Chicago Press, Chicago & London. https://books.google.com.tr/books?id=S0tgwgEACAAJ
  34. Yi, W. & Özdamar, L. (2007). A dynamic logistics coordination model for evacuation and support in disaster response activities, European Journal of Operational Research, Elsevier, 179(3), 1177-1193. Doi: https://doi.org/10.1016/j.ejor.2005.03.077
  35. Ağdaş, M., Bali, Ö. & Ballı, H. (2014). Afet lojistiği kapsamında dağıtım merkezi için yer seçimi: SMAA-2 tekniği ile bir uygulama. Beykoz Akademi Dergisi, 2(1), 75-94. issue/52159/682113.
  36. Durak, İ. & Yıldız, M. S. (2015). P-Medyan Tesis Yeri Seçim Problemi: Bir Uygulama. Uluslararası Alanya İşletme Fakültesi Dergisi, Antalya, Türkiye.
  37. Gencer, C. & Açıkgöz, A. (2006). Türk Silahlı Kuvvetleri arama kurtarma timlerinin yerleşiminin yeniden düzenlenmesi. Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, 21(1), 87-105. /issue/6667/88813
  38. Karabay, S., Köse, E. & Kabak, M. (2014). Stokastik çok kriterli kabul edilebilirlik analizi ile bir kamu kurumu için tesis yeri seçimi. Ege Akademik Bakış, 14(3), 361-369
  39. Kurban, Ö. & Can, T. (2016). Acil istihbarat, gözetleme ve keşif ihtiyaçları için mini insansız hava araçlarının yer kontrol istasyonlarının seçimi. Öneri Dergisi, 12(45), 35-59.
  40. Sarıkaya, H. A., Aygüneş, H. & Kılıç. A. (2020). Jandarma karakollarının yer seçiminin enbüyük kapsama metodu ile belirlenmesi. Endüstri Mühendisliği, 31 (1), 28-47. endustrimuhendisligi/ issue/53786/603442