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COVID-19 VE GELECEKTEKİ DİĞER PANDEMİLER İÇİN ÇKKV TEKNİKLERİYLE BİR SAHRA HASTANESİNİN YERİNİN BELİRLENMESİ

Yıl 2022, Cilt: 9 Sayı: 17, 345 - 359, 31.08.2022
https://doi.org/10.54365/adyumbd.1070522

Öz

Bu çalışma, Avrupa Birliği ülkeleri arasındaki hızlı virüs yayılımında yetersiz kalan sağlık hizmetlerinin iyileştirilmesi, geliştirilmesi ve desteklenmesi amacıyla yapılmıştır. Bu çalışmada, başta Avrupa Birliği ülkeleri olmak üzere COVID-19 pandemisi ve gelecekte olabilecek pandemi durumlarında pandemiden en çok etkilenen nüfusa hizmet verecek bir sahra hastanesinin yerinin belirlenmesi amaçlanmıştır. Potansiyel bir sahra hastanesinin yerini belirlemek için 5 ana ve 20 alt kriterli çok kriterli bir karar modeli önerilmiş ve altı aday Avrupa Birliği ülkesi bu alt kriterlere göre değerlendirilmiştir. Problemin çözüm aşamasında iki adet çok kriterli karar verme yöntemi sırayla kullanılmış, öncelikle SWARA yöntemi ile seçim kriterlerinin önem ağırlıkları belirlenmiş ve ikinci olarak EDAS yöntemi ile alternatif ülkeler değerlendirilmiş ve sıralanmıştır.

Kaynakça

  • Budak F, Korkmaz Ş. An overall evaluation for the COVID-19 pandemic process: The case of Turkey. Journal of Social Research and Management 2020; 1: 62-79.
  • Agarwal S, Kant R, Shankar R. Evaluating solutions to overcome humanitarian supply chain management barriers: A hybrid fuzzy SWARA – Fuzzy WASPAS approach. International Journal of Disaster Risk Reduction 2020; 51: 101838.
  • Mostafaeipour A, Dehshiri SJH, Dehshiri SSH. Ranking locations for producing hydrogen using geothermal energy in Afghanistan. International Journal of Hydrogen Energy 2020; 45(32): 15924-15940.
  • Shao M, Han Z, Sun J, Xiao C, Zhang S, Zhao Y. A review of multi-criteria decision making applications for renewable energy site selection. Renewable Energy 2020; 157: 377-403.
  • Ulutas A, Karakus CB, Topal A. Location selection for logistics center with fuzzy SWARA and CoCoSo methods. Journal of Intelligent and Fuzzy Systems 2020; 38(1): 1-17.
  • Popovic G, Stanujkic D, Brzakovic M, Karabasevic D. A multiple-criteria decision-making model for the selection of a hotel location. Land Use Policy 2019; 84: 49-58.
  • Mostafaeipour A, Dehshiri SJH, Dehshiri SSH, Jahangiri M. Prioritization of potential locations for harnessing wind energy to produce hydrogen in Afghanistan. International Journal of Hydrogen Energy 2020; 45(58): 33169-33184.
  • Supciller AA, Toprak F. Selection of wind turbines with multi-criteria decision making techniques involving neutrosophic numbers: A case from Turkey. Energy 2020; 207: 118237.
  • Dahooie JH, Dehshiri SJH, Banaitis A, Binkyte-Veliene A. Identifying and prioritizing cost reduction solutions in supply chain by integrating value endineering and gray multi-criteria decision-making. Technological and Economic Development of Economy 2020; 26(6): 1311-1338.
  • Ghorabaee MK, Amiri M, Zavadskas EK, Antucheviciene J. A new hybrid fuzzy MCDM approach for evaluation of construction equipment with sustainability considerations. Archives of Civil and Mechanical Engineering 2018; 18(1): 32-49.
  • Juodagalviene B, Turskis Z, Saparauskas J, Endriukaityte A. Integrated multi-criteria evaluation of house’s plan shape based on the EDAS and SWARA methods. Engineering Structures and Technologies 2017; 9(3): 117–125.
  • Ghorabaee MK, Amiri M, Zavadskas EK, Turskis Z, Antucheviciene J. A new hybrid simulation-based assignment approach for evaluating airlines with multiple service quality criteria. Journal of Air Transport Management 2017; 63: 45-60.
  • Samanlıoğlu F, Kaya BE. Evaluation of the COVID-19 Pandemic Intervention Strategies with Hesitant F-AHP. Journal of Healthcare Engineering 2020; Article ID 8835258.
  • Gül S. Fermatean fuzzy set extensions of SAW, ARAS, andVIKOR with applications in COVID-19 testing laboratoryselection problem. Expert Systems 2021; 38: 12769.
  • Moradian MJ, Ardalan A, Nejati A, Bloorani AD, Akbari AB, Rastegarfar B. Field hospital site selection criteria: A Delphi consensus study. International Journal of Emergency Management 2018; 14(4): 377.
  • Aydın N, Şeker Ş. Determining the location of isolation hospitals for COVID-19 via Delphi-based MCDM method. International Journal of Intelligent Systtems 2021; 36: 3011–3034.
  • Gül M, Güneri AF. Hospital Location Selection: A Systematic Literature Review on Methodologies and Applications. Mathematical Problems in Engineering 2021; Article ID 6682958.
  • World Health Organization Europe, https://www.euro.who.int/en/health-topics/health-emergencies/coronavirus-covid-19/novel-coronavirus-2019-ncov. Arrival Date: 20.03.2021.
  • World Health Organization, https://covid19.who.int/. Arrival Date: 08.02.2022.
  • Statistica, https://www.statista.com/. Arrival Date: 15.03.2021.
  • Şen H, Demiral MF. Hospital Location Selection with Grey System Theory. European Journal of Economics and Business Studies 2016; 2(2): 66-79.
  • Chatterjee D, Mukherjee B. Potential Hospital Location Selection Using Fuzzy-AHP: An Empirical Study in Rural India. International Journal of Computer Applications 2013; 71(17): 1-7.
  • Moradian MJ, Ardalan A, Nejati A, Boloorani AD, Akbarisari A, Rastegarfar B. Risk Criteria in Hospital Site Selection: A Systematic Review. PLoS Currents 2017; 9.
  • Rahimi F, Goli A, Rezaee R. Hospital location-allocation in Shiraz using Geographical Information System (GIS). Shiraz E-Medical Journal 2017; 18(8): 57572.
  • Assad CAR. Building GIS Framework based on Multi Criteria Analysis for Hospital Site Selection in Developing Countries. International Journal of Computer Techniques 2019; 6(4): 1-6.
  • Kim JI, Senaratna DM, Ruza J, Kam C, Ng S. Feasibility Study on an Evidence-Based Decision-Support System for Hospital Site Selection for an Aging Population. Sustainability 2015; 7(3): 2730-2744.
  • Kahraman C, Gündogdu FK, Onar SC, Oztaysi B. Hospital Location Selection Using Spherical Fuzzy TOPSIS. Atlantis Studies in Uncertainty Modelling 1. 11th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT 2019), 2019: 77-82.
  • Keršulienė V, Zavadskas EK, Turskis Z. Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management 2010; 11(2): 243–258.
  • Prajapati H, Kant R, Shankar R. Prioritizing the solutions of reverse logistics implementation to mitigate its barriers: A hybrid modified SWARA and WASPAS approach. Journal of Cleaner Production 2019; 240: 118219.
  • Balki MK, Erdoğan S, Aydın S, Sayin C. The optimization of engine operating parameters via SWARA and ARAS hybrid method in a small SI engine using alternative fuel. Journal of Cleaner Production 2020; 258: 120685.
  • Ghorabaee MK, Zavadskas EK, Olfat L, Turskis Z. Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (EDAS). Informatica 2015; 26: 435-451.
  • Yazdani M, Torkayesh AE, Santibanez-Gonzalez EDR, Otaghsara SK. Evaluation of renewable energy resources using integrated Shannon Entropy—EDAS model. Sustainable Operations and Computers 2020; 1: 35-42.
  • Abdel-Basset M, Gamal A, Chakrabortty RK, Ryan MJ. Evaluation of sustainable hydrogen production options using an advanced hybrid MCDM approach: A case study. International Journal of Hydrogen Energy 2021; 46(5): 4567-4591.

DETERMINATION OF A FIELD HOSPITAL LOCATION WITH MCDM TECHNIQUES FOR COVID-19 AND ANY OTHER PANDEMICS IN FUTURE

Yıl 2022, Cilt: 9 Sayı: 17, 345 - 359, 31.08.2022
https://doi.org/10.54365/adyumbd.1070522

Öz

This study was carried out to improve, develop and support the health services that are insufficient in the rapid virus spread between the European Union countries. In this study, it is aimed to determine the location of a field hospital that will serve the patients of the European Union countries, especially the population most affected by the pandemic, in the case of the COVID-19 pandemic and the possible pandemics that may occur. A multi criteria decision model was proposed with 5 main and 20 sub-criteria in order to determine the location of a potential field hospital and six candidate European Union countries were evaluated according to these sub-criteria. In the solution phase of the problem two multi-criteria decision making methods are used in a sequence, firstly the importance weights of the selection criteria were determined with SWARA method and secondly the alternative countries were evaluated and ranked with EDAS method.

Kaynakça

  • Budak F, Korkmaz Ş. An overall evaluation for the COVID-19 pandemic process: The case of Turkey. Journal of Social Research and Management 2020; 1: 62-79.
  • Agarwal S, Kant R, Shankar R. Evaluating solutions to overcome humanitarian supply chain management barriers: A hybrid fuzzy SWARA – Fuzzy WASPAS approach. International Journal of Disaster Risk Reduction 2020; 51: 101838.
  • Mostafaeipour A, Dehshiri SJH, Dehshiri SSH. Ranking locations for producing hydrogen using geothermal energy in Afghanistan. International Journal of Hydrogen Energy 2020; 45(32): 15924-15940.
  • Shao M, Han Z, Sun J, Xiao C, Zhang S, Zhao Y. A review of multi-criteria decision making applications for renewable energy site selection. Renewable Energy 2020; 157: 377-403.
  • Ulutas A, Karakus CB, Topal A. Location selection for logistics center with fuzzy SWARA and CoCoSo methods. Journal of Intelligent and Fuzzy Systems 2020; 38(1): 1-17.
  • Popovic G, Stanujkic D, Brzakovic M, Karabasevic D. A multiple-criteria decision-making model for the selection of a hotel location. Land Use Policy 2019; 84: 49-58.
  • Mostafaeipour A, Dehshiri SJH, Dehshiri SSH, Jahangiri M. Prioritization of potential locations for harnessing wind energy to produce hydrogen in Afghanistan. International Journal of Hydrogen Energy 2020; 45(58): 33169-33184.
  • Supciller AA, Toprak F. Selection of wind turbines with multi-criteria decision making techniques involving neutrosophic numbers: A case from Turkey. Energy 2020; 207: 118237.
  • Dahooie JH, Dehshiri SJH, Banaitis A, Binkyte-Veliene A. Identifying and prioritizing cost reduction solutions in supply chain by integrating value endineering and gray multi-criteria decision-making. Technological and Economic Development of Economy 2020; 26(6): 1311-1338.
  • Ghorabaee MK, Amiri M, Zavadskas EK, Antucheviciene J. A new hybrid fuzzy MCDM approach for evaluation of construction equipment with sustainability considerations. Archives of Civil and Mechanical Engineering 2018; 18(1): 32-49.
  • Juodagalviene B, Turskis Z, Saparauskas J, Endriukaityte A. Integrated multi-criteria evaluation of house’s plan shape based on the EDAS and SWARA methods. Engineering Structures and Technologies 2017; 9(3): 117–125.
  • Ghorabaee MK, Amiri M, Zavadskas EK, Turskis Z, Antucheviciene J. A new hybrid simulation-based assignment approach for evaluating airlines with multiple service quality criteria. Journal of Air Transport Management 2017; 63: 45-60.
  • Samanlıoğlu F, Kaya BE. Evaluation of the COVID-19 Pandemic Intervention Strategies with Hesitant F-AHP. Journal of Healthcare Engineering 2020; Article ID 8835258.
  • Gül S. Fermatean fuzzy set extensions of SAW, ARAS, andVIKOR with applications in COVID-19 testing laboratoryselection problem. Expert Systems 2021; 38: 12769.
  • Moradian MJ, Ardalan A, Nejati A, Bloorani AD, Akbari AB, Rastegarfar B. Field hospital site selection criteria: A Delphi consensus study. International Journal of Emergency Management 2018; 14(4): 377.
  • Aydın N, Şeker Ş. Determining the location of isolation hospitals for COVID-19 via Delphi-based MCDM method. International Journal of Intelligent Systtems 2021; 36: 3011–3034.
  • Gül M, Güneri AF. Hospital Location Selection: A Systematic Literature Review on Methodologies and Applications. Mathematical Problems in Engineering 2021; Article ID 6682958.
  • World Health Organization Europe, https://www.euro.who.int/en/health-topics/health-emergencies/coronavirus-covid-19/novel-coronavirus-2019-ncov. Arrival Date: 20.03.2021.
  • World Health Organization, https://covid19.who.int/. Arrival Date: 08.02.2022.
  • Statistica, https://www.statista.com/. Arrival Date: 15.03.2021.
  • Şen H, Demiral MF. Hospital Location Selection with Grey System Theory. European Journal of Economics and Business Studies 2016; 2(2): 66-79.
  • Chatterjee D, Mukherjee B. Potential Hospital Location Selection Using Fuzzy-AHP: An Empirical Study in Rural India. International Journal of Computer Applications 2013; 71(17): 1-7.
  • Moradian MJ, Ardalan A, Nejati A, Boloorani AD, Akbarisari A, Rastegarfar B. Risk Criteria in Hospital Site Selection: A Systematic Review. PLoS Currents 2017; 9.
  • Rahimi F, Goli A, Rezaee R. Hospital location-allocation in Shiraz using Geographical Information System (GIS). Shiraz E-Medical Journal 2017; 18(8): 57572.
  • Assad CAR. Building GIS Framework based on Multi Criteria Analysis for Hospital Site Selection in Developing Countries. International Journal of Computer Techniques 2019; 6(4): 1-6.
  • Kim JI, Senaratna DM, Ruza J, Kam C, Ng S. Feasibility Study on an Evidence-Based Decision-Support System for Hospital Site Selection for an Aging Population. Sustainability 2015; 7(3): 2730-2744.
  • Kahraman C, Gündogdu FK, Onar SC, Oztaysi B. Hospital Location Selection Using Spherical Fuzzy TOPSIS. Atlantis Studies in Uncertainty Modelling 1. 11th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT 2019), 2019: 77-82.
  • Keršulienė V, Zavadskas EK, Turskis Z. Selection of rational dispute resolution method by applying new step-wise weight assessment ratio analysis (SWARA). Journal of Business Economics and Management 2010; 11(2): 243–258.
  • Prajapati H, Kant R, Shankar R. Prioritizing the solutions of reverse logistics implementation to mitigate its barriers: A hybrid modified SWARA and WASPAS approach. Journal of Cleaner Production 2019; 240: 118219.
  • Balki MK, Erdoğan S, Aydın S, Sayin C. The optimization of engine operating parameters via SWARA and ARAS hybrid method in a small SI engine using alternative fuel. Journal of Cleaner Production 2020; 258: 120685.
  • Ghorabaee MK, Zavadskas EK, Olfat L, Turskis Z. Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (EDAS). Informatica 2015; 26: 435-451.
  • Yazdani M, Torkayesh AE, Santibanez-Gonzalez EDR, Otaghsara SK. Evaluation of renewable energy resources using integrated Shannon Entropy—EDAS model. Sustainable Operations and Computers 2020; 1: 35-42.
  • Abdel-Basset M, Gamal A, Chakrabortty RK, Ryan MJ. Evaluation of sustainable hydrogen production options using an advanced hybrid MCDM approach: A case study. International Journal of Hydrogen Energy 2021; 46(5): 4567-4591.
Toplam 33 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Makaleler
Yazarlar

G.nilay Yücenur 0000-0002-2670-6277

Yayımlanma Tarihi 31 Ağustos 2022
Gönderilme Tarihi 9 Şubat 2022
Yayımlandığı Sayı Yıl 2022 Cilt: 9 Sayı: 17

Kaynak Göster

APA Yücenur, G. (2022). DETERMINATION OF A FIELD HOSPITAL LOCATION WITH MCDM TECHNIQUES FOR COVID-19 AND ANY OTHER PANDEMICS IN FUTURE. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi, 9(17), 345-359. https://doi.org/10.54365/adyumbd.1070522
AMA Yücenur G. DETERMINATION OF A FIELD HOSPITAL LOCATION WITH MCDM TECHNIQUES FOR COVID-19 AND ANY OTHER PANDEMICS IN FUTURE. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi. Ağustos 2022;9(17):345-359. doi:10.54365/adyumbd.1070522
Chicago Yücenur, G.nilay. “DETERMINATION OF A FIELD HOSPITAL LOCATION WITH MCDM TECHNIQUES FOR COVID-19 AND ANY OTHER PANDEMICS IN FUTURE”. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi 9, sy. 17 (Ağustos 2022): 345-59. https://doi.org/10.54365/adyumbd.1070522.
EndNote Yücenur G (01 Ağustos 2022) DETERMINATION OF A FIELD HOSPITAL LOCATION WITH MCDM TECHNIQUES FOR COVID-19 AND ANY OTHER PANDEMICS IN FUTURE. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi 9 17 345–359.
IEEE G. Yücenur, “DETERMINATION OF A FIELD HOSPITAL LOCATION WITH MCDM TECHNIQUES FOR COVID-19 AND ANY OTHER PANDEMICS IN FUTURE”, Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi, c. 9, sy. 17, ss. 345–359, 2022, doi: 10.54365/adyumbd.1070522.
ISNAD Yücenur, G.nilay. “DETERMINATION OF A FIELD HOSPITAL LOCATION WITH MCDM TECHNIQUES FOR COVID-19 AND ANY OTHER PANDEMICS IN FUTURE”. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi 9/17 (Ağustos 2022), 345-359. https://doi.org/10.54365/adyumbd.1070522.
JAMA Yücenur G. DETERMINATION OF A FIELD HOSPITAL LOCATION WITH MCDM TECHNIQUES FOR COVID-19 AND ANY OTHER PANDEMICS IN FUTURE. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi. 2022;9:345–359.
MLA Yücenur, G.nilay. “DETERMINATION OF A FIELD HOSPITAL LOCATION WITH MCDM TECHNIQUES FOR COVID-19 AND ANY OTHER PANDEMICS IN FUTURE”. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi, c. 9, sy. 17, 2022, ss. 345-59, doi:10.54365/adyumbd.1070522.
Vancouver Yücenur G. DETERMINATION OF A FIELD HOSPITAL LOCATION WITH MCDM TECHNIQUES FOR COVID-19 AND ANY OTHER PANDEMICS IN FUTURE. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi. 2022;9(17):345-59.