Araştırma Makalesi
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Kamusal Acil Durum Senaryoları için Karar Destek Aracı Önerisi

Yıl 2022, Cilt: 3 Sayı: 2, 197 - 218, 30.09.2022
https://doi.org/10.53710/jcode.1144777

Öz

Çeşitli acil durum veya doğal afet koşulları gündelik yaşamın sürdürülmesi, refah, sağlık, ekonomi ve stratejik planlama ve yönetim gibi hayatın birden çok yönünü etkileyen göz ardı edilemez sonuçlar doğurmaktadır. Bu gibi olağandışı durumların neden olduğu sorunlarla mücadele etmek, her birinin kendine özgü acil durum plan ve operasyonları gerektirmesi sebebiyle zorlu olabilmektedir. Öte yandan çok çeşitli olası acil durum senaryolarında bile, herkes için ortak bir zorluk vardır: erişilebilirlik. Çalışmanın amacı iş yükü, karmaşıklık ve zaman yönetimi nedeniyle acil durumlarda müdahale çözümlerini etkileyebilecek ve geciktirebilecek insani faktörleri olabildiğince ortadan kaldırmayı hedeflemenin yanı sıra, müdahale aşamasında tesislerin erişilebilirliği ve tesis sayısının yetersiz olma hali sebebiyle meydana gelebilecek sorunların kriz anında üstesinden gelmektir. Bu çalışma, acil durum senaryolarında sürdürülebilir yaşam için temel hususları belirleyerek, öncelikli olarak vazgeçilemez geçici tesisleri stratejik olarak tahsis etmek için herhangi bir acil durum senaryosu için kullanılabilecek bir karar destek aracı önererek, olağanüstü durumlarda bile refahı ve sürdürülebilir bir günlük yaşamı güvence altına alacak bir yöntem önermektedir. Olağandışı durumlar her koşulda tesislere erişim için zorluklara sebep olur ve bu gibi durumlarda tesislerin erişilebilir mesafelerde ve yeterli sayıda temin edilebilmesi hayati önem taşımaktadır. Önerilen araç, acil durum yönetimlerinin müdahale aşamasında nüfus yoğunluğunu dikkate alarak karşılanamayan talepler için mümkün olan en az mesafede geçici tesisler sağlamayı hedeflemektedir. Olası bir senaryoyu ortaya koymak için bir sel vakası üzerinden olay örneği yapılmıştır.

Kaynakça

  • Abulnour, A., H. (2014). The post-disaster temporary dwelling: Fundamentals of provision, design and construction. Housing and Building National Research Center. 10(1), 10-24. https://doi.org/10.1016/j.hbrcj.2013.06.001
  • Altay, N. and Green, G., W. (2006). OR/MS Research in disaster operations management. European Journal of Operational Research. 175, 475-493. https://doi.org/10.1016/j.ejor.2005.05.016
  • Balcik, B., & Beamon, B. M. (2008). Facility location in humanitarian relief. International Journal of Logistics: Research and Applications, 11(2), 101-121. http://dx.doi.org/10.1080/13675560701561789
  • Brown, G.G., & Vassiliou, A.L. (1993). Optimizing disaster relief: real-time operational and tactical decision support. Naval Research Logistics, 40, 1-23. DOI:10.1002/1520-6750(199302)40:1<1::AID-NAV3220400102>3.0.CO;2-S
  • Çavdur, F., Kose-Kucuk, M., Sebatli, A. (2016). Allocation of temporary disaster response facilities under demand uncertainty: An earthquake case study. International Journal of Disaster Risk Reduction, 19, 159-166. https://doi.org/10.1016/j.ijdrr.2016.08.009
  • Cavdur, F. and Sebatli, A. (2019). A decision support tool for allocating temporary-disaster-response facilities. Decision Support Systems, 127. https://doi.org/10.1016/j.dss.2019.113145
  • Cavdur, F., Sebatli-Saglam, A., Kose-Kucuk, M. (2020). A spreadsheet-based decision support tool for temporary-disaster-response facilities allocation. Safety Science, 124. https://doi.org/10.1016/j.ssci.2019.104581
  • Civil Contingencies Secretariat (2004). Civil Contingencies Act 2004: a short guide (revised). Civil Contingencies Secretariat. https://www.merseysideprepared.org.uk/media/1053/15mayshortguide.pdf
  • Jianshe, D., Shuning, W., and Xiaoyin, Y. (1994). Computerized support systems for emergency decision making. Annals of Operations Research. 51, 313–325. https://doi.org/10.1007/BF02048553
  • Kovács, G. and Spens, K.M. (2007). Humanitarian logistics in disaster relief operations. International Journal of Physical Distribution & Logistics Management, 37(2), 99-114. https://doi.org/10.1108/09600030710734820
  • Leiras, A., Brito, I.D., Peres, E.Q., Bertazzo, T.R., & Yoshizaki, H.T. (2014). Literature review of humanitarian logistics research: trends and challenges. Journal of Humanitarian Logistics and Supply Chain Management, 4(1), 95-130. DOI:10.1108/JHLSCM-04-2012-0008.
  • Lopez-Fuentes, L., van de Weijer, J., González-Hidalgo, M. et al. (2018). Review on computer vision techniques in emergency situations. Multimed Tools Appl, 77, 17107. https://doi.org/10.1007/s11042-017-5276-7
  • Oksuz, M.K., & Satoglu, S.I. (2020). A two-stage stochastic model for location planning of temporary medical centers for disaster response. International journal of disaster risk reduction, 44, 101426. https://doi.org/10.1016/j.ijdrr.2019.101426
  • Rolland, E., Patterson, R.A., Ward, K. et al. (2010). Decision support for disaster management. Operations Management Research. 3, 68–79. https://doi.org/10.1007/s12063-010-0028-0
  • Sebatli, A., Çavdur, F., Kose-Kucuk, M. (2017). Determination of relief supplies demands and allocation of temporary disaster response facilities. Transportation Research Procedia, 22, 245-254. https://doi.org/10.1016/j.trpro.2017.03.031
  • Thompson, S.A., Altay, N., Green, W.G., & Lapetina, J.E. (2006). Improving disaster response efforts with decision support systems. International Journal of Emergency Management, 3(4), 250-263. doi:10.1504/IJEM.2006.011295
  • Tuğba Turğut, B., Taş, G., Herekoğlu, A., Tozan, H. and Vayvay, O. (2011). A fuzzy AHP based decision support system for disaster center location selection and a case study for Istanbul. Disaster Prevention and Management, 20(5), 499-520. https://doi.org/10.1108/09653561111178943
  • Van de Walle, B., Turoff, M. (2008). Decision support for emergency situations. Inf Syst E-Bus Manage 6, 295–316. https://doi.org/10.1007/s10257-008-0087-z

A Decision Support Tool Proposal for Public Emergency Scenarios

Yıl 2022, Cilt: 3 Sayı: 2, 197 - 218, 30.09.2022
https://doi.org/10.53710/jcode.1144777

Öz

Every day the world is facing a possible emergency or disaster scenario that affects the basis of ordinary life as we know such as natural disasters such as earthquakes or floods, or a vast viral epidemic that alters the way we live. Public emergency scenarios shift the way of living, and ramifications of ongoing or post-emergency issues related to extraordinary circumstances affect many aspects such as sustaining everyday life, welfare, health, economy, and more that require strategic planning and management. The impacts of such emergencies are so massive and extended in almost every aspect of human lives that it is impossible to overlook. Even with the wide range of possible emergency scenarios, there is a common challenge for all: accessibility. Extraordinary circumstances cause potential difficulties for access to facilities in any case and supplying facilities in a considerably short distance. An adequate number can be a matter of life and death. Tackling the issues caused by emergencies might be challenging because each entails unique contingency plans and managing operations. However, for all the emergency scenarios, one of the most crucial common matters is the accessibility to facilities. Coming up with a good comprehensive strategy that functions as a decision support system is crucial to eliminating human factors that may affect and delay response solutions for emergencies due to workload, complexity, and time management. The study aims to overcome the inadequate number of facilities during the time of crisis in the response phase to emergencies that may occur due to the accessibility of facilities. Through identifying critical considerations for sustainable life in emergency scenarios, this paper proposes an approach to assure welfare and a sustainable daily life even in extraordinary circumstances through proposing a decision support tool. This support tool can be used for any emergency scenario to strategically allocate indispensable temporary facility structures that can be accessible for all people at a minimum possible distance according to relevant emergency conditions' necessities. It generates to provide and allocate temporary facilities for unmet demand by considering population density in the response phase of emergency management. A case of a flood is issued to demonstrate a possible scenario. The final section discusses the proposed tool's contingency plan possibilities, constraints, and feasibility.

Kaynakça

  • Abulnour, A., H. (2014). The post-disaster temporary dwelling: Fundamentals of provision, design and construction. Housing and Building National Research Center. 10(1), 10-24. https://doi.org/10.1016/j.hbrcj.2013.06.001
  • Altay, N. and Green, G., W. (2006). OR/MS Research in disaster operations management. European Journal of Operational Research. 175, 475-493. https://doi.org/10.1016/j.ejor.2005.05.016
  • Balcik, B., & Beamon, B. M. (2008). Facility location in humanitarian relief. International Journal of Logistics: Research and Applications, 11(2), 101-121. http://dx.doi.org/10.1080/13675560701561789
  • Brown, G.G., & Vassiliou, A.L. (1993). Optimizing disaster relief: real-time operational and tactical decision support. Naval Research Logistics, 40, 1-23. DOI:10.1002/1520-6750(199302)40:1<1::AID-NAV3220400102>3.0.CO;2-S
  • Çavdur, F., Kose-Kucuk, M., Sebatli, A. (2016). Allocation of temporary disaster response facilities under demand uncertainty: An earthquake case study. International Journal of Disaster Risk Reduction, 19, 159-166. https://doi.org/10.1016/j.ijdrr.2016.08.009
  • Cavdur, F. and Sebatli, A. (2019). A decision support tool for allocating temporary-disaster-response facilities. Decision Support Systems, 127. https://doi.org/10.1016/j.dss.2019.113145
  • Cavdur, F., Sebatli-Saglam, A., Kose-Kucuk, M. (2020). A spreadsheet-based decision support tool for temporary-disaster-response facilities allocation. Safety Science, 124. https://doi.org/10.1016/j.ssci.2019.104581
  • Civil Contingencies Secretariat (2004). Civil Contingencies Act 2004: a short guide (revised). Civil Contingencies Secretariat. https://www.merseysideprepared.org.uk/media/1053/15mayshortguide.pdf
  • Jianshe, D., Shuning, W., and Xiaoyin, Y. (1994). Computerized support systems for emergency decision making. Annals of Operations Research. 51, 313–325. https://doi.org/10.1007/BF02048553
  • Kovács, G. and Spens, K.M. (2007). Humanitarian logistics in disaster relief operations. International Journal of Physical Distribution & Logistics Management, 37(2), 99-114. https://doi.org/10.1108/09600030710734820
  • Leiras, A., Brito, I.D., Peres, E.Q., Bertazzo, T.R., & Yoshizaki, H.T. (2014). Literature review of humanitarian logistics research: trends and challenges. Journal of Humanitarian Logistics and Supply Chain Management, 4(1), 95-130. DOI:10.1108/JHLSCM-04-2012-0008.
  • Lopez-Fuentes, L., van de Weijer, J., González-Hidalgo, M. et al. (2018). Review on computer vision techniques in emergency situations. Multimed Tools Appl, 77, 17107. https://doi.org/10.1007/s11042-017-5276-7
  • Oksuz, M.K., & Satoglu, S.I. (2020). A two-stage stochastic model for location planning of temporary medical centers for disaster response. International journal of disaster risk reduction, 44, 101426. https://doi.org/10.1016/j.ijdrr.2019.101426
  • Rolland, E., Patterson, R.A., Ward, K. et al. (2010). Decision support for disaster management. Operations Management Research. 3, 68–79. https://doi.org/10.1007/s12063-010-0028-0
  • Sebatli, A., Çavdur, F., Kose-Kucuk, M. (2017). Determination of relief supplies demands and allocation of temporary disaster response facilities. Transportation Research Procedia, 22, 245-254. https://doi.org/10.1016/j.trpro.2017.03.031
  • Thompson, S.A., Altay, N., Green, W.G., & Lapetina, J.E. (2006). Improving disaster response efforts with decision support systems. International Journal of Emergency Management, 3(4), 250-263. doi:10.1504/IJEM.2006.011295
  • Tuğba Turğut, B., Taş, G., Herekoğlu, A., Tozan, H. and Vayvay, O. (2011). A fuzzy AHP based decision support system for disaster center location selection and a case study for Istanbul. Disaster Prevention and Management, 20(5), 499-520. https://doi.org/10.1108/09653561111178943
  • Van de Walle, B., Turoff, M. (2008). Decision support for emergency situations. Inf Syst E-Bus Manage 6, 295–316. https://doi.org/10.1007/s10257-008-0087-z
Toplam 18 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Yazılım Testi, Doğrulama ve Validasyon
Bölüm Araştırma Makaleleri
Yazarlar

Tuğçe Gökçen

Belinda Torus 0000-0003-0699-3421

Yayımlanma Tarihi 30 Eylül 2022
Yayımlandığı Sayı Yıl 2022 Cilt: 3 Sayı: 2

Kaynak Göster

APA Gökçen, T., & Torus, B. (2022). A Decision Support Tool Proposal for Public Emergency Scenarios. Journal of Computational Design, 3(2), 197-218. https://doi.org/10.53710/jcode.1144777

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