TOPSIS Yöntemine Dayalı Öğrenci Sağlık Merkezi Yeri Seçimi: Bir Üniversite Uygulaması

Yıl 2021, Cilt: 23 Sayı: 69, 823 - 833, 15.09.2021

Muhammet Enes Akpınar , Kamil Koçak

https://doi.org/10.21205/deufmd.2021236910

Öz

Öğrenci sağlık merkezi için yer seçimi özellikle son yıllarda dikkate alınması gereken önemli konulardan biridir. Artan öğrenci yoğunluğu ve genişleyen kampüsler olası bir acil durumda ilk yardımın yapılabilmesi açısından bu ihtiyacının ne kadar önemli olduğunu göstermektedir. Sıradan ve öğrenci yoğunluğundan uzak noktalara yapılacak bir öğrenci sağlık merkezi ve müdahale gerektiren durumlarda müdahalenin yapılamaması beraberinde birçok problemi getirebilmektedir. Bu problemden hareketle bu çalışmada öğrenci sağlık merkezi yer seçimi için bir gerçek hayat uygulaması yapılmıştır. Yapılan bu uygulamada öncelikle öğrencilerin bulunduğu kampüs noktalara ayrılmıştır. Sonrasında bu noktalar gruplandırılarak öğrenci sağlık merkezi için alternatif yerler ağırlık merkezi yöntemine göre belirlenmiştir. Belirlenen alternatifler ve öğrenci sağlık merkezi kriterleri TOPSIS yöntemi kullanılarak çözülmüştür. Çalışma sonucunda kriterleri tatmin eden en uygun alternatif nokta seçilmiştir.

Anahtar Kelimeler

Çok kriterli karar verme, TOPSIS yöntemi, Öğrenci sağlık merkezi, Yer seçimi

Student Health Centre Site Selection Based on Multi-Criteria Decision Making Method: A University Application

Öz

Deciding a place for a student health center is one of the important issues to be taken into account especially in recent years. Increasing student density and expanding campuses show how important this need is in terms of providing first aid in a possible emergency. A student health center to be built in places far from ordinary and student density, and failure to intervene in situations requiring intervention can bring many problems. Based on this problem, in this study, a real life application was made for student health center location selection. In this application, the campus where the students are located is divided into points. Afterwards, these points were grouped and alternative places for the student health center were determined according to the center of gravity method. The determined alternatives and student health center criteria were solved using the TOPSIS method. At the end of the study, the most suitable alternative point satisfying the criteria was selected.

Anahtar Kelimeler

Multi criteria decision making, TOPSIS method, Student health centre, Site selection

Kaynakça

• Chen, K., Blong, R., Jacobson, C., (2001). MCE-RISK: integrating multicriteria evaluation and GIS for risk decision-making in natural hazards. Environmental Modelling and Software, 16, 387-397.
• Healey, M., Ilbery, B., (1990). Location and Change: Perspectives on Economic Geography. Oxford University Press.
• İnce Ö, Bedir N, Eren T., (2016). Hastane kuruluş yeri seçimi probleminin analitik hiyerarşi süreci ile modellenmesi: Tuzla ilçesi uygulaması. Gazi Üniversitesi Sağlık Bilimleri Dergisi;1(3):08–21.
• Chiu JE, Tsai HH., (2013). In: Applying analytic hierarchy process to select optimal ex- pansion of hospital location, the case of a Regional Teaching Hospital in Yunlin;p. 2013. doi: 10.1109/ICSSSM.6602588.
• Wu CR , Lin CT , Chen HC., (2007). Optimal selection of location for Taiwanese hospitals to ensure a competitive advantage by using the analytic hierarchy process and sensitivity analysis. Build Environment;42:1431–44.
• Wu CR , Lin CT , Chen HC., (2009). Integrated environmental assessment of the location selection with fuzzy analytical network process. Qual Quant;43:351–80.
• Vahidnia MH, Alesheikh AA, Alimohammadi A., (2009). Hospital site selection using fuzzy AHP and its derivatives. J Environ Manage; 90(10):3048–56.
• Murad AA., (2007). Creating a GIS application for health services at Jeddah city. Comput Bio Med;37:879–89.
• Sharmin N , Neema MN., (2013). A GIS-based multi-criteria analysis to site appropriate locations of hospitals in Dhaka City. Hospital (Rio J);8:0–37.
• Rahimi F, Goli A, Rezaee R., (2017). Hospital location-allocation in Shiraz using geo- graphical information system (GIS). Shiraz E-Med J;18(8):e57572. doi: 10. 5812/semj.57572.
• Sipahi, S., Timor, M., (2010). The analytic hierarchy process and analytic network process: an overview of applications. Management Decision 48(5), 775–808. doi: 10.1108/00251741011043920.
• Zhang W , Cao K , Liu S , Huang B., (2016). A multi-objective optimization approach for health-care facility location-allocation problems in highly developed cities such as Hong Kong. Comput Environ Urban Syst;59:220–30.
• Velasquez M , Hester PT., (2013). An analysis of multi-criteria decision making methods. Int J Oper Res;10(2):56–66.
• Dyer JS., (2005). Multiattribute Utility Theory. In: Greco S, Ehrgott M, Figueira J, editors. Multiple criteria decision Analysis: state of the art surveys. New York: Springer;p. 265–92.
• Chen, C. T., Lin, C. T., Huang, S. F., (2006). A fuzzy approach for supplier evaluationand selection in supply chain management.International Journal of ProductionEconomics, 102, 289–301.
• Banaeian, N., Mobli, H., Fahimnia, B., Nielsen, I. E., & Omid, M., (2018). Green supplier selection using fuzzy group decision making methods: A case study from the agri-food industry. Computers & Operations Research, 89, 337-347.
• Wang Chen, H. M., Chou, S. Y., Luu, Q. D., Yu, T. H. K., (2016). A fuzzy MCDM approach for green supplier selection from the economic and environmental aspects. Mathematical Problems in Engineering, 1-10.
• Wang, W. P., (2009). Toward developing agility evaluation of mass customization systems using 2-tuple linguistic computing. Expert Systems with Applications, 36, 3439–3447.
• Shih, H. S., (2008). Incremental analysis for MCDM with an application to group TOPSIS. European Journal of Operational Research, 186, 720–734
• Alimoradi, A., Yussuf, R. M., Zulkifli, N., (2011). A hybrid model for remanufacturing facility location problem in a closed-loop supply chain. International Journal of Sustainable Engineering, 4(1), 16–23.
• Awasthi, A., Chauhan, S. S., Omrani, H., Panahi, A., (2011). A hybrid approachbased on SERVQUAL and fuzzy TOPSIS for evaluating transportation servicequality. Computers & Industrial Engineering, 61, 637–646.
• Kuo, M. S., (2011). Optimal location selection for an international distributioncenter by using a new hybrid method. Expert Systems with Applications, 38,7208–7221.
• Kuo, M. S., Liang, G. S., (2011). A novel hybrid decision-making model for selectinglocations in a fuzzy environment. Mathematical and Computer Modeling, 54,88–104.
• Ning, X., Lam, K. C., Lam, M. C. K., (2011). A decision-making system for construction site layout planning. Automation in Construction, 20, 459–473.
• Vijay M. A., Shankar, C., (2010). A TOPSIS Method-based Approach to Machine Tool selection. Proceedings of the 2010 International Conference on Industrial Engineering and Operations Management Dhaka, Bangladesh, January 9 –10.
• Moghassem, A. R., (2010). Application of TOPSIS approach on parameters selectionproblem for rotor spinning machine.Fibers and Polymers, 11(4), 669–675.
• Behzadian, M., Otaghsara, S. K., Yazdani, M., Ignatius, J., (2012). A state-of the-art survey of TOPSIS applications. Expert Systems with applications, 39(17), 13051-13069.
• Ahmed A, Mahmoud H, Aly AMM., (2016). Site suitability evaluation for sustainable distribution of hospital using spatial information technologies and AHP: a case study of upper Egypt, Aswan City. J Geography Information Syst;8:578–94.
• Hwang, C. L., Yoon, K., (1981). Multiple attributes decision-making methods and applications. Heideberg: Springer.
• Chen, P., (2019). Effects of normalization on the entropy-based TOPSIS method. Expert Systems with Applications, 136(1),33-41.
• M. A. Cherier, M. Bennekrouf and S. M. Meliani, "The Application of AHP-TOPSIS Methodology for Selection of Agriculture Farms in Tomato Processing Industry: Algerian Case Study," 2020 IEEE 13th International Colloquium of Logistics and Supply Chain Management (LOGISTIQUA), Fez, Morocco, 2020, pp. 1-5, doi: 10.1109/LOGISTIQUA49782.2020.9353915.
• Y. S. Bagi, S. Suyono and M. F. Tomatala, "Decision Support System for High Achieving Students Selection Using AHP and TOPSIS," 2020 2nd International Conference on Cybernetics and Intelligent System (ICORIS), Manado, Indonesia, 2020, pp. 1-5, doi: 10.1109/ICORIS50180.2020.9320823.
• S. A. Shaikh, M. A. Memon, M. Prokop and K. Kim, "An AHP/TOPSIS-Based Approach for an Optimal Site Selection of a Commercial Opening Utilizing GeoSpatial Data," 2020 IEEE International Conference on Big Data and Smart Computing (BigComp), Busan, Korea (South), 2020, pp. 295-302, doi: 10.1109/BigComp48618.2020.00-58.
• A. D. Setiawan, A. Hidayatno, B. D. Putra and I. Rahman, "Selection of Charging Station Technology to Support the Adoption of Electric Vehicles in Indonesia with the AHP-TOPSIS Method," 2020 3rd International Conference on Power and Energy Applications (ICPEA), Busan, Korea (South), 2020, pp. 85-88, doi: 10.1109/ICPEA49807.2020.9280125.
• M. A. Nazari, M. E. Haj Assad, S. Haghighat and A. Maleki, "Applying TOPSIS Method for Wind Farm Site Selection in Iran," 2020 Advances in Science and Engineering Technology International Conferences (ASET), Dubai, United Arab Emirates, 2020, pp. 1-4, doi: 10.1109/ASET48392.2020.9118223.
• Baranitharan, P., Ramesh, K., Sakthivel, R., (2019). Multi-attribute decision-making approach for Aegle marmelos pyrolysis process using TOPSIS and Grey Relational Analysis: Assessment of engine emissions through novel Infrared thermography. Journal of Cleaner Production, 234 (2019) 315-328.
• Farias Aires, R. F., Ferreira, L. (2019). A new approach to avoid rank reversal cases in the TOPSIS method. Computers & Industrial Engineering, 132, 84-97.
• Romesburg, C. (2004). Cluster analysis for researchers. Lulu Press.
• K. Winarso, S. Akhmad, R. Hidayat and A. Arendra, "Determining The Location Point of Aggregation Warehouse for Salt Supply Chain," 2020 6th Information Technology International Seminar (ITIS), Surabaya, Indonesia, 2020, pp. 188-192, doi: 10.1109/ITIS50118.2020.9320963.
• A. Rautela, S. K. Sharma, and P. Bhardwaj, “Vehicle routing approach for an efficient distribution: A case of a state-owned Indian cooperative dairy,” Int. J. Procure. Manag., vol. 10, no. 6, pp. 776–789, 2017, doi: 10.1504/IJPM.2017.087319.