Araştırma Makalesi
BibTex RIS Kaynak Göster

Afet Sonrası İnsani Yardım Lojistiğinde Stokastik Talepli Araç Rotalama Problemi için Çözüm Yöntemleri

Yıl 2025, Cilt: 10 Sayı: 2, 222 - 235, 11.11.2025

Engin Baytürk , Beyzanur Turna , İrem Saka , Aysuma Kaya

https://doi.org/10.26650/JTL.2025.1610468

Öz

Afet yönetimi, afetlerin verdiği büyük yıkımların önlenebilmesinde önem taşımaktadır. Afet yönetimi, afet gerçekleşmeden önce, afet anında ve afet gerçekleştikten sonra alınan tedbirler olarak ana aşamalara ayrılmaktadır. Özellikle, afet sonrasında yapılan planlamaların en önemlilerinden biri afet sonrası insani yardım lojistiğidir. Bu kapsamda, insani yardım lojistiği, afetten etkilenen insanların gereksinimlerini giderebilmek için, afet gerçekleştikten sonra gerekecek olan doğru bilginin, temel gereksinimlerin, ekipmanların gereken zamanda, gereken yere ve gerekli kişilere temin etme sürecidir. Afet yönetimi lojistik süreçleri afet öncesi gerekli önlemlerin alınması, acil müdahale ve iyileştirme aşamalarından oluşmaktır. Afet yönetiminde lojistik süreçlerin temelinin oluşmasını sağlayan bu adımlar afetten etkilenenler için gereken ürünlerin lojistiğin bir temeli olarak da bilinen gereken zamanda, gereken yerde, gerekli miktarda, uygun koşullarda, en uygun maliyetle, gereken kişilere temin edilmesinde etkin bir rol almaktadır. Tüm bu önemli etkilerinden dolayı, bu çalışmada afet sonrasında insani yardım lojistiğinin doğru şekilde sağlanabilmesi için araç rotalama problemi ile ilgili karma tam sayılı matematiksel model ve k-ortalamalar ile karınca kolonisi optimizasyonunun kullanıldığı matematiksel modeller oluşturulmuştur. Bu modellerde talepler stokastik olarak gerçekleşmektedir ve araçlar tarafından kullanılabilir olan yol durumları senaryo bazlı olarak değişkenlik göstermektedir. Oluşturulan modeller, Hatay ilinin Defne ilçesinde afet sonrası yardım lojistiği alanında uygulamaya konulmuştur.

Anahtar Kelimeler

Afet Lojistiği Araç Rotalama İnsani Yardım Lojistiği

Etik Beyan

Çalışmanın tüm süreçlerinin araştırma ve yayın etiğine uygun olduğunu, etik kurallara ve bilimsel atıf gösterme ilkelerine uyduğumu beyan ederim.

Kaynakça

  • Ablanedo-Rosas, J. H., Gao, H., Alidaee, B., & Teng, W. Y. (2009). Allocation of emergency and recovery centres in Hidalgo, Mexico. International Journal of Services Sciences, 2(2), 206-218. doi:https://doi.org/10.1504/IJSSCI.2009.024941 google scholar
  • Ablanedo-Rosas, J. H., Gao, H., Alidaee, B., & Teng, W. Y. (2009). Allocation of emergency and recovery centres in Hidalgo, Mexico. International Journal of Services Sciences, 2(2), 206-218. https://doi.org/l0.1504/IJSSCI.2009.024941 google scholar
  • 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), 75-95. google scholar
  • Babaei, A., & Shahanaghi, K. (2017). A new model for planning the distributed facility locations under emergencY conditions and uncertainty space in relief logistics. Uncertain Supply Chain Management, 5, 105-125. https://doi.org/10.5267/j.uscm.2016.10.004 google scholar
  • Barbarosoğlu, G., & Arda, Y. (2004). A two-stage stochastic programming framework for transportation planning in disaster response. Journal of the Operational Research SocietY, 55, 43-53. https://doi.org/10.1057/palgrave.jors.2601652 google scholar
  • Barbarosoğlu, G., Özdamar, L., & Çevik, A. (2002). An interactive approach for hierarchical analysis of helicopter logistics in disaster relief operations. European Journal of Operational Research, 140(1), 118-133. google scholar
  • Bell, J. E., & McMullen, P. R. (2004). Ant colony optimization techniques for the vehicle routing problem. Advanced Engineering Infor-matics, 18, 41-48. google scholar
  • Cura, T. (2008). Modern sezgisel teknikler ve uygulamaları (1. Baskı). PapatYa Yayıncılık. google scholar
  • Desrochers, M., Desrosiers, J., & Solomon, M. M. (1992). A new optimization algorithm for the vehicle routing problem with time windows. Operations Research, 40(2), 342-354. https://doi.org/10.1287/opre.40.2.342 google scholar
  • ErsoY, P. ve Börühan, G. (2013). Lojistik süreçler açısından afet lojistiğinin önemi. Finans Politik ve Ekonomik Yorumlar, 50(578), 75-86. google scholar
  • Garrido, R. A., Lamas, P., & Pino, F. J. (2015). A stochastic programming approach for flood emergency logistics. Transportation Research Part E: Logistics and Transportation Review, 75, 18-31. https://doi.org/10.1016/j.tre.2014.12.002 google scholar
  • Günneç, D., & Salman, F. S. (2011). Assessing the reliabilitY and the expected performance of a network under disaster risk. OR Spectrum, 33(3), 499-523. https://doi.org/10.1007/s00291-011-0250-7 google scholar
  • Huang, R., Kim, S., & Menezes, M. B. (2010). FacilitY location for large-scale emergencies. Annals of Operations Research, 181(1), 271-286. https://doi.org/10.1007/s10479-010-0736-8 google scholar
  • Hu, S. L., Han, C. F. ve Meng, L. P. (2017). Stochastic optimization for joint decision making of inventory and procurement in humanitarian relief. Computers ve Industrial Engineering, 111, 39-49. https://doi.org/10.1016/j.cie.2017.06.029 google scholar
  • Jha, A., AcharYa, D., & Tiwar, M. K. (2017). Humanitarian relief supplY chain: a multi-objective model and solution. Sadhana, 42(7), 1167 1174. https://doi.org/10.1007/s12046-017-0679-8 google scholar
  • Kovacs, G., & Spens, K. M. (2012). Relief supplY chain for disasters, humanitarian aid and emergency logistics. Business Science, USA. google scholar
  • Laporte, G. (1992). The vehicle routing problem: An overview of exact and approximate algorithms. European Journal of Operational Research, 59(3), 345-358. https://doi.org/10.1016/0377-2217(92)90192-C google scholar Lee, Y. M., Ghosh, S., & Ettl, M. (2009). Simulating the distribution of emergency relief supplies for disaster response operations. Proceedings of the 2009 Winter Simulation Conference. https://doi.org/10.1109/WSC.2009.5429246 google scholar
  • Li, X., Ramshani, M., & Huang, Y. (2018). Cooperative maximal covering models for humanitarian relief chain management. Computers ve Industrial Engineering, 119, 301-308. https://doi.org/10.1016/j.cie.2018.04.004 google scholar
  • Lloyd, S. (1982). Least squares quantization in PCM. IEEE Transactions on Information Theory, 28(2), 129-137. https://doi.org/10.1109/TIT.1982.1056489 google scholar
  • Lu, C. C. (2013). Robust weighted vertex p-center model considering uncertain data: Application to emergency management. European Journal of Operational Research, 230(1), 113-121. https://doi.org/10.1016/j.ejor.2013.03.028 google scholar
  • Lu, X. L., & Hou, Y. X. (2009). Ant colony optimization for facilitY location for large-scale emergencies. In Management and Service Science. 2009 International Conference on Management and Service Science. https://doi.org/10.1109/ICMSS.2009.5302451 google scholar
  • Manopiniwes, W., & Irohara, T. (2017). Stochastic optimisation model for integrated decisions on relief supply chains: Preparedness for disaster response. International Journal of Production Research, 55(4), 979-996. https://doi.org/10.1080/00207543.2016.1211340 google scholar
  • Massaguer, D., Balasubramanian, V., Mehrotra, S., & Venkatasubramanian, N. (2006). Multi-agent simulation of disaster response. Erişim adresi: https://www.researchgate.net/publication/241438415 google scholar
  • Miller, C. E., Tucker, A. W., & Zemlin, R. A. (1960). Integer programming formulation of the traveling salesman problem. Journal of the ACM (JACM), 7(4), 326-329. https://doi.org/10.1145/321043.321046 google scholar
  • Özdamar, L., Ekinci, E., & KüçükYazici, B. (2004). Emergency logistics planning in natural disasters. Annals of Operations Research, 129(1-4), 217-245. https://doi.org/10.1023/B:ANOR.0000030690.27939.39 google scholar
  • Safaei, A. S., Farsad, S., & PaYdar, M. M. (2018). Emergency logistics planning under supply risk and demand uncertainty. Operational Research International Journal, 1-24. google scholar
  • Sheu, J. B. (2007). Afetlerde acil Yardım talebine hızlı Yanıt için acil lojistik dağıtım Yaklaşımı. Ulaştırma Araştırması Bölüm E: Lojistik ve Ulaştırma İncelemesi, 43(6), 687-709. google scholar
  • Soyöz, H., & ÖzYörük, B. (2021). Afet lojistiğinde üç aşamalı karma tamsayılı bir model önerisi. Journal of Turkish Operations Management, 5(1), 641-661. google scholar
  • Şen, G., & Esmer, S. (2017). Afet lojistiği: Bir literatür taraması. The International New Issues in Social Sciences, 5, 231-250. google scholar
  • Torabi, S. A., Shokr, I., Tofighi, S., & Heydari, J. (2018). Integrated relief pre-positioning and procurement planning in humanitarian supply chains. Transportation Research Part E, 113, 123-146. https://doi.org/10.1016/j.tre.2018.03.012 google scholar
  • Toth, P., & Vigo, D. (2014). Vehicle Routing: Problems, Methods, and Applications (2nd ed.). Society for Industrial and Applied Mathematics (SIAM). https://doi.org/10.1137/1.9781611973594 google scholar
  • V erma, A., & Gaukler, G. M. (2011). A stochastic optimization model for positioning disaster response facilities for large-scale emergen-cies. International Conference on Network Optimization, 547-552. google scholar
  • V itoriano, B., Ortuno, M. T., Tirado, G., & Montero, J. (2011). A multi-criteria optimization model for humanitarian aid distribution. Journal of Global Optimization, 51, 189-208. https://doi.org/10.1007/s10898-010-9603-z google scholar
  • Yadav, D. K., & Barve, A. (2015). Analysis of Critical Success Factors of Humanitarian Supply Chain: An Application of Interpretive Structural Modeling. International Journal of Disaster Risk Reduction, 12, 213-225. Journal of Transportation and Logistics google scholar

Solution Methods for Vehicle Routing Problem with Stochastic Demand in Post-Disaster Humanitarian Logistics

Yıl 2025, Cilt: 10 Sayı: 2, 222 - 235, 11.11.2025

Engin Baytürk , Beyzanur Turna , İrem Saka , Aysuma Kaya

https://doi.org/10.26650/JTL.2025.1610468

Öz

Disaster management plays a critical role in minimizing destruction caused by disasters and is typically divided into three stages: preparedness, response, and recovery. Among these, post-disaster humanitarian aid logistics is essential for effectively addressing the immediate needs of affected populations. This process involves delivering accurate information, basic necessities, and critical equipment to the right people, at the right time and place. The logistics components of disaster management include taking precautions before the disaster, providing rapid emergency response, and ensuring long-term recovery. These phases form the foundation of humanitarian logistics, ensuring the timely, efficient, and cost-effective distribution of aid under varying conditions. In this study, mathematical models were developed to optimize post-disaster humanitarian logistics using a mixed-integer programming model, k-means clustering, and ant colony optimization for solving the vehicle routing problem. The models incorporate stochastic demand and scenario-based road accessibility to reflect realistic post-disaster conditions. The proposed approach was applied to the Defne district of Hatay province, a region affected by a recent disaster. The results aim to improve the delivery of humanitarian aid by enhancing route planning and distribution efficiency under uncertainty, contributing to more effective disaster response and recovery operations.

Anahtar Kelimeler

Disaster logistics Vehicle routing Humanitarian logistics

Kaynakça

  • Ablanedo-Rosas, J. H., Gao, H., Alidaee, B., & Teng, W. Y. (2009). Allocation of emergency and recovery centres in Hidalgo, Mexico. International Journal of Services Sciences, 2(2), 206-218. doi:https://doi.org/10.1504/IJSSCI.2009.024941 google scholar
  • Ablanedo-Rosas, J. H., Gao, H., Alidaee, B., & Teng, W. Y. (2009). Allocation of emergency and recovery centres in Hidalgo, Mexico. International Journal of Services Sciences, 2(2), 206-218. https://doi.org/l0.1504/IJSSCI.2009.024941 google scholar
  • 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), 75-95. google scholar
  • Babaei, A., & Shahanaghi, K. (2017). A new model for planning the distributed facility locations under emergencY conditions and uncertainty space in relief logistics. Uncertain Supply Chain Management, 5, 105-125. https://doi.org/10.5267/j.uscm.2016.10.004 google scholar
  • Barbarosoğlu, G., & Arda, Y. (2004). A two-stage stochastic programming framework for transportation planning in disaster response. Journal of the Operational Research SocietY, 55, 43-53. https://doi.org/10.1057/palgrave.jors.2601652 google scholar
  • Barbarosoğlu, G., Özdamar, L., & Çevik, A. (2002). An interactive approach for hierarchical analysis of helicopter logistics in disaster relief operations. European Journal of Operational Research, 140(1), 118-133. google scholar
  • Bell, J. E., & McMullen, P. R. (2004). Ant colony optimization techniques for the vehicle routing problem. Advanced Engineering Infor-matics, 18, 41-48. google scholar
  • Cura, T. (2008). Modern sezgisel teknikler ve uygulamaları (1. Baskı). PapatYa Yayıncılık. google scholar
  • Desrochers, M., Desrosiers, J., & Solomon, M. M. (1992). A new optimization algorithm for the vehicle routing problem with time windows. Operations Research, 40(2), 342-354. https://doi.org/10.1287/opre.40.2.342 google scholar
  • ErsoY, P. ve Börühan, G. (2013). Lojistik süreçler açısından afet lojistiğinin önemi. Finans Politik ve Ekonomik Yorumlar, 50(578), 75-86. google scholar
  • Garrido, R. A., Lamas, P., & Pino, F. J. (2015). A stochastic programming approach for flood emergency logistics. Transportation Research Part E: Logistics and Transportation Review, 75, 18-31. https://doi.org/10.1016/j.tre.2014.12.002 google scholar
  • Günneç, D., & Salman, F. S. (2011). Assessing the reliabilitY and the expected performance of a network under disaster risk. OR Spectrum, 33(3), 499-523. https://doi.org/10.1007/s00291-011-0250-7 google scholar
  • Huang, R., Kim, S., & Menezes, M. B. (2010). FacilitY location for large-scale emergencies. Annals of Operations Research, 181(1), 271-286. https://doi.org/10.1007/s10479-010-0736-8 google scholar
  • Hu, S. L., Han, C. F. ve Meng, L. P. (2017). Stochastic optimization for joint decision making of inventory and procurement in humanitarian relief. Computers ve Industrial Engineering, 111, 39-49. https://doi.org/10.1016/j.cie.2017.06.029 google scholar
  • Jha, A., AcharYa, D., & Tiwar, M. K. (2017). Humanitarian relief supplY chain: a multi-objective model and solution. Sadhana, 42(7), 1167 1174. https://doi.org/10.1007/s12046-017-0679-8 google scholar
  • Kovacs, G., & Spens, K. M. (2012). Relief supplY chain for disasters, humanitarian aid and emergency logistics. Business Science, USA. google scholar
  • Laporte, G. (1992). The vehicle routing problem: An overview of exact and approximate algorithms. European Journal of Operational Research, 59(3), 345-358. https://doi.org/10.1016/0377-2217(92)90192-C google scholar Lee, Y. M., Ghosh, S., & Ettl, M. (2009). Simulating the distribution of emergency relief supplies for disaster response operations. Proceedings of the 2009 Winter Simulation Conference. https://doi.org/10.1109/WSC.2009.5429246 google scholar
  • Li, X., Ramshani, M., & Huang, Y. (2018). Cooperative maximal covering models for humanitarian relief chain management. Computers ve Industrial Engineering, 119, 301-308. https://doi.org/10.1016/j.cie.2018.04.004 google scholar
  • Lloyd, S. (1982). Least squares quantization in PCM. IEEE Transactions on Information Theory, 28(2), 129-137. https://doi.org/10.1109/TIT.1982.1056489 google scholar
  • Lu, C. C. (2013). Robust weighted vertex p-center model considering uncertain data: Application to emergency management. European Journal of Operational Research, 230(1), 113-121. https://doi.org/10.1016/j.ejor.2013.03.028 google scholar
  • Lu, X. L., & Hou, Y. X. (2009). Ant colony optimization for facilitY location for large-scale emergencies. In Management and Service Science. 2009 International Conference on Management and Service Science. https://doi.org/10.1109/ICMSS.2009.5302451 google scholar
  • Manopiniwes, W., & Irohara, T. (2017). Stochastic optimisation model for integrated decisions on relief supply chains: Preparedness for disaster response. International Journal of Production Research, 55(4), 979-996. https://doi.org/10.1080/00207543.2016.1211340 google scholar
  • Massaguer, D., Balasubramanian, V., Mehrotra, S., & Venkatasubramanian, N. (2006). Multi-agent simulation of disaster response. Erişim adresi: https://www.researchgate.net/publication/241438415 google scholar
  • Miller, C. E., Tucker, A. W., & Zemlin, R. A. (1960). Integer programming formulation of the traveling salesman problem. Journal of the ACM (JACM), 7(4), 326-329. https://doi.org/10.1145/321043.321046 google scholar
  • Özdamar, L., Ekinci, E., & KüçükYazici, B. (2004). Emergency logistics planning in natural disasters. Annals of Operations Research, 129(1-4), 217-245. https://doi.org/10.1023/B:ANOR.0000030690.27939.39 google scholar
  • Safaei, A. S., Farsad, S., & PaYdar, M. M. (2018). Emergency logistics planning under supply risk and demand uncertainty. Operational Research International Journal, 1-24. google scholar
  • Sheu, J. B. (2007). Afetlerde acil Yardım talebine hızlı Yanıt için acil lojistik dağıtım Yaklaşımı. Ulaştırma Araştırması Bölüm E: Lojistik ve Ulaştırma İncelemesi, 43(6), 687-709. google scholar
  • Soyöz, H., & ÖzYörük, B. (2021). Afet lojistiğinde üç aşamalı karma tamsayılı bir model önerisi. Journal of Turkish Operations Management, 5(1), 641-661. google scholar
  • Şen, G., & Esmer, S. (2017). Afet lojistiği: Bir literatür taraması. The International New Issues in Social Sciences, 5, 231-250. google scholar
  • Torabi, S. A., Shokr, I., Tofighi, S., & Heydari, J. (2018). Integrated relief pre-positioning and procurement planning in humanitarian supply chains. Transportation Research Part E, 113, 123-146. https://doi.org/10.1016/j.tre.2018.03.012 google scholar
  • Toth, P., & Vigo, D. (2014). Vehicle Routing: Problems, Methods, and Applications (2nd ed.). Society for Industrial and Applied Mathematics (SIAM). https://doi.org/10.1137/1.9781611973594 google scholar
  • V erma, A., & Gaukler, G. M. (2011). A stochastic optimization model for positioning disaster response facilities for large-scale emergen-cies. International Conference on Network Optimization, 547-552. google scholar
  • V itoriano, B., Ortuno, M. T., Tirado, G., & Montero, J. (2011). A multi-criteria optimization model for humanitarian aid distribution. Journal of Global Optimization, 51, 189-208. https://doi.org/10.1007/s10898-010-9603-z google scholar
  • Yadav, D. K., & Barve, A. (2015). Analysis of Critical Success Factors of Humanitarian Supply Chain: An Application of Interpretive Structural Modeling. International Journal of Disaster Risk Reduction, 12, 213-225. Journal of Transportation and Logistics google scholar
Toplam 34 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Ulaşım, Lojistik ve Tedarik Zincirleri (Diğer)
Bölüm Araştırma Makalesi
Yazarlar

Engin Baytürk 0000-0001-9860-1581

Beyzanur Turna 0009-0000-4943-1854

İrem Saka 0009-0006-3145-2626

Aysuma Kaya 0009-0003-3396-4156

Yayımlanma Tarihi 11 Kasım 2025
Gönderilme Tarihi 31 Aralık 2024
Kabul Tarihi 10 Nisan 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 10 Sayı: 2

Kaynak Göster

APA Baytürk, E., Turna, B., Saka, İ., Kaya, A. (2025). Afet Sonrası İnsani Yardım Lojistiğinde Stokastik Talepli Araç Rotalama Problemi için Çözüm Yöntemleri. Journal of Transportation and Logistics, 10(2), 222-235. https://doi.org/10.26650/JTL.2025.1610468
AMA Baytürk E, Turna B, Saka İ, Kaya A. Afet Sonrası İnsani Yardım Lojistiğinde Stokastik Talepli Araç Rotalama Problemi için Çözüm Yöntemleri. JTL. Kasım 2025;10(2):222-235. doi:10.26650/JTL.2025.1610468
Chicago Baytürk, Engin, Beyzanur Turna, İrem Saka, ve Aysuma Kaya. “Afet Sonrası İnsani Yardım Lojistiğinde Stokastik Talepli Araç Rotalama Problemi için Çözüm Yöntemleri”. Journal of Transportation and Logistics 10, sy. 2 (Kasım 2025): 222-35. https://doi.org/10.26650/JTL.2025.1610468.
EndNote Baytürk E, Turna B, Saka İ, Kaya A (01 Kasım 2025) Afet Sonrası İnsani Yardım Lojistiğinde Stokastik Talepli Araç Rotalama Problemi için Çözüm Yöntemleri. Journal of Transportation and Logistics 10 2 222–235.
IEEE E. Baytürk, B. Turna, İ. Saka, ve A. Kaya, “Afet Sonrası İnsani Yardım Lojistiğinde Stokastik Talepli Araç Rotalama Problemi için Çözüm Yöntemleri”, JTL, c. 10, sy. 2, ss. 222–235, 2025, doi: 10.26650/JTL.2025.1610468.
ISNAD Baytürk, Engin vd. “Afet Sonrası İnsani Yardım Lojistiğinde Stokastik Talepli Araç Rotalama Problemi için Çözüm Yöntemleri”. Journal of Transportation and Logistics 10/2 (Kasım2025), 222-235. https://doi.org/10.26650/JTL.2025.1610468.
JAMA Baytürk E, Turna B, Saka İ, Kaya A. Afet Sonrası İnsani Yardım Lojistiğinde Stokastik Talepli Araç Rotalama Problemi için Çözüm Yöntemleri. JTL. 2025;10:222–235.
MLA Baytürk, Engin vd. “Afet Sonrası İnsani Yardım Lojistiğinde Stokastik Talepli Araç Rotalama Problemi için Çözüm Yöntemleri”. Journal of Transportation and Logistics, c. 10, sy. 2, 2025, ss. 222-35, doi:10.26650/JTL.2025.1610468.
Vancouver Baytürk E, Turna B, Saka İ, Kaya A. Afet Sonrası İnsani Yardım Lojistiğinde Stokastik Talepli Araç Rotalama Problemi için Çözüm Yöntemleri. JTL. 2025;10(2):222-35.
 Kapak Resmi İndir