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Bulanık Choquet İntegral Yöntemini Kullanarak Bir Covid-19 Sahra Hastanesi İçin Yer Seçimi

Year 2021, Volume: 12 Issue: 3, 1095 - 1109, 25.09.2021

Abstract

COVID-19 salgını sırasında sahra hastanelerine olan ihtiyaç büyük ölçüde artmıştır. Bir sahra hastanesinin yeri, hastaların hastaneye erişimini doğrudan etkilediği için yetkililerin aldığı muhtemelen en kritik karardır. Bu çalışma, Türkiye'nin üçüncü büyük şehri olan İzmir'de kurulacak COVID-19 sahra hastanesi için en uygun konumu belirlemeyi amaçlamaktadır. Dilsel değerlendirmelere izin veren bir çok kriterli karar verme tekniği olan Bulanık Choquet Integrali, sahra hastanesi için alternatif konumları değerlendirmek için kullanılmıştır. Bu yöntem ayrıca kriterler arasındaki etkileşimi de dikkate alarak genel bir ağırlık elde etmektedir. Bununla birlikte karar vericilerin her bir kriteri değerlendirirken aralıklı değerler kullanabilmesi öznel karar verme aşamasındaki hataları ortadan kaldırmaktadır. Yöntemde son olarak her bir kriterin hangi alternatif için en iyi tercih edilebileceği sonucu da elde edilebilmektedir. Çalışmada, İzmir'deki dört alternatif konumun (Bornova, Karşıyaka, Konak ve Buca) genel ağırlık değerleri belirlenmiş ve en yüksek genel ağırlık değerine sahip olan Bornova alternatifi en uygun konum olarak önerilmiştir.

References

  • Adalı, E. A., & Tuş, A. (2019). Hospital site selection with distance-based multi-criteria decision-making methods. International Journal of Healthcare Management, 1-11.
  • Auephanwiriyakul, S., Keller, J. M., & Gader, P. D. (2002). Generalized Choquet fuzzy integral fusion. Information fusion, 3(1), 69-85.
  • Aydin, N. (2016). A stochastic mathematical model to locate field hospitals under disruption uncertainty for large-scale disaster preparedness. An International Journal of Optimization and Control: Theories & Applications (IJOCTA), 6(2), 85-102.
  • Behzadi, S., & Alesheikh, A. A. (2013). Hospital site selection using a BDI agent model. International Journal of Geography and Geology, 2(4), 36-51.
  • Delgado, M., Herrera, F., Herrera-Viedma, E., & Martinez, L. (1998). Combining numerical and linguistic information in group decision making. Information Sciences, 107(1-4), 177-194.
  • Fortemps, P., & Roubens, M. (1996). Ranking and defuzzification methods based on area compensation. Fuzzy sets and systems, 82(3), 319-330.
  • Kim, J. I., Senaratna, D. M., Ruza, J., Kam, C., & Ng, S. (2015). Feasibility study on an evidence-based decision-support system for hospital site selection for an aging population. Sustainability, 7(3), 2730-2744.
  • Kumar, P., Singh, R. K., & Sinha, P. (2016). Optimal site selection for a hospital using a fuzzy extended ELECTRE approach. Journal of Management Analytics, 3(2), 115-135.
  • Kutlu G. F., Kahraman, C., & Civan, H. N. (2018). A novel hesitant fuzzy EDAS method and its application to hospital selection. Journal of Intelligent & Fuzzy Systems, 35(6), 6353-6365.
  • Lin, C. T., & Tsai, M. C. (2010). Location choice for direct foreign investment in new hospitals in China by using ANP and TOPSIS. Quality & Quantity, 44(2), 375-390.
  • Pınar, M. İ. Ç., & ANTMEN, Z. F. (2019). A Healthcare Facility Location Selection Problem with Fuzzy TOPSIS Method for a Regional Hospital. Avrupa Bilim ve Teknoloji Dergisi, (16), 750-757.
  • Miç, P., & Antmen, Z. F. (2019). Sağlık Hizmeti Tesis Yerleşimi Probleminin Değerlendirilmesine Çok Kriterli Bulanık Bir Yaklaşım. European Journal of Science and Technology, 16, 750-757.
  • Moradian, M. J., Ardalan, A., Nejati, A., Boloorani, A. D., Akbarisari, A., & Rastegarfar, B. (2017). Risk criteria in hospital site selection: a systematic review. PLoS currents, 9.
  • Şahin, T., Ocak, S., & Top, M. (2019). Analytic hierarchy process for hospital site selection. Health Policy and Technology, 8(1), 42-50.
  • Senvar, O., Otay, I., & Bolturk, E. (2016). Hospital site selection via hesitant fuzzy TOPSIS. IFAC-PapersOnLine, 49(12), 1140-1145.
  • Tsai, H. H., & Lu, I. Y. (2006). The evaluation of service quality using generalized Choquet integral. Information Sciences, 176(6), 640-663.
  • Vahidnia, M. H., Alesheikh, A. A., & Alimohammadi, A. (2009). Hospital site selection using fuzzy AHP and its derivatives. Journal of environmental management, 90(10), 3048-3056.
  • Zolfani, S., Yazdani, M., Ebadi Torkayesh, A., & Derakhti, A. (2020). Application of a gray-based decision support framework for location selection of a temporary hospital during COVID-19 pandemic. Symmetry, 12(6), 886.

Location Selection for a Covid-19 Field Hospital Using Fuzzy Choquet Integral Method

Year 2021, Volume: 12 Issue: 3, 1095 - 1109, 25.09.2021

Abstract

The need for field hospitals increased drastically during COVID-19 pandemic. Location of a field hospital is probably the most critical decision taken by government authorities since it directly affect the patients' access to the hospital. This study aims to determine the most suitable location for a COVID-19 field hospital to be constructed in İzmir, the third largest city of Turkey. Fuzzy Choquet integral multi criteria decision making technique that allows for linguistic assessments is used to evaluate the alternative locations for the field hospital. This method also obtains a general weight by taking into account the interaction between the criteria. Besides, decision-makers can use interval values while evaluating each criterion and thus this process eliminates errors in subjective decision-making. Moreover it is also possible to obtain the result for which alternative is the best preferred for each of criterion. Overall weight values of four alternative locations in İzmir (i.e., Bornova, Karsiyaka, Konak and Buca) were determined and Bornova alternative with the highest overall weight value was proposed as the most suitable location for the field hospital.

References

  • Adalı, E. A., & Tuş, A. (2019). Hospital site selection with distance-based multi-criteria decision-making methods. International Journal of Healthcare Management, 1-11.
  • Auephanwiriyakul, S., Keller, J. M., & Gader, P. D. (2002). Generalized Choquet fuzzy integral fusion. Information fusion, 3(1), 69-85.
  • Aydin, N. (2016). A stochastic mathematical model to locate field hospitals under disruption uncertainty for large-scale disaster preparedness. An International Journal of Optimization and Control: Theories & Applications (IJOCTA), 6(2), 85-102.
  • Behzadi, S., & Alesheikh, A. A. (2013). Hospital site selection using a BDI agent model. International Journal of Geography and Geology, 2(4), 36-51.
  • Delgado, M., Herrera, F., Herrera-Viedma, E., & Martinez, L. (1998). Combining numerical and linguistic information in group decision making. Information Sciences, 107(1-4), 177-194.
  • Fortemps, P., & Roubens, M. (1996). Ranking and defuzzification methods based on area compensation. Fuzzy sets and systems, 82(3), 319-330.
  • Kim, J. I., Senaratna, D. M., Ruza, J., Kam, C., & Ng, S. (2015). Feasibility study on an evidence-based decision-support system for hospital site selection for an aging population. Sustainability, 7(3), 2730-2744.
  • Kumar, P., Singh, R. K., & Sinha, P. (2016). Optimal site selection for a hospital using a fuzzy extended ELECTRE approach. Journal of Management Analytics, 3(2), 115-135.
  • Kutlu G. F., Kahraman, C., & Civan, H. N. (2018). A novel hesitant fuzzy EDAS method and its application to hospital selection. Journal of Intelligent & Fuzzy Systems, 35(6), 6353-6365.
  • Lin, C. T., & Tsai, M. C. (2010). Location choice for direct foreign investment in new hospitals in China by using ANP and TOPSIS. Quality & Quantity, 44(2), 375-390.
  • Pınar, M. İ. Ç., & ANTMEN, Z. F. (2019). A Healthcare Facility Location Selection Problem with Fuzzy TOPSIS Method for a Regional Hospital. Avrupa Bilim ve Teknoloji Dergisi, (16), 750-757.
  • Miç, P., & Antmen, Z. F. (2019). Sağlık Hizmeti Tesis Yerleşimi Probleminin Değerlendirilmesine Çok Kriterli Bulanık Bir Yaklaşım. European Journal of Science and Technology, 16, 750-757.
  • Moradian, M. J., Ardalan, A., Nejati, A., Boloorani, A. D., Akbarisari, A., & Rastegarfar, B. (2017). Risk criteria in hospital site selection: a systematic review. PLoS currents, 9.
  • Şahin, T., Ocak, S., & Top, M. (2019). Analytic hierarchy process for hospital site selection. Health Policy and Technology, 8(1), 42-50.
  • Senvar, O., Otay, I., & Bolturk, E. (2016). Hospital site selection via hesitant fuzzy TOPSIS. IFAC-PapersOnLine, 49(12), 1140-1145.
  • Tsai, H. H., & Lu, I. Y. (2006). The evaluation of service quality using generalized Choquet integral. Information Sciences, 176(6), 640-663.
  • Vahidnia, M. H., Alesheikh, A. A., & Alimohammadi, A. (2009). Hospital site selection using fuzzy AHP and its derivatives. Journal of environmental management, 90(10), 3048-3056.
  • Zolfani, S., Yazdani, M., Ebadi Torkayesh, A., & Derakhti, A. (2020). Application of a gray-based decision support framework for location selection of a temporary hospital during COVID-19 pandemic. Symmetry, 12(6), 886.
There are 18 citations in total.

Details

Primary Language English
Journal Section Articles
Authors

Muhammet Enes Akpınar 0000-0003-0328-6107

Mehmet Ali Ilgın 0000-0003-1765-2470

Publication Date September 25, 2021
Submission Date May 22, 2021
Published in Issue Year 2021 Volume: 12 Issue: 3

Cite

APA Akpınar, M. E., & Ilgın, M. A. (2021). Location Selection for a Covid-19 Field Hospital Using Fuzzy Choquet Integral Method. Gümüşhane Üniversitesi Sosyal Bilimler Dergisi, 12(3), 1095-1109. https://doi.org/10.36362/gumus.941097