Research Article
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Year 2025, Volume: 10 Issue: 2, 244 - 261
https://doi.org/10.26833/ijeg.1596244

Abstract

References

  • Ohba, T., Tanigawa, K., Liutsko, L. (2021). Evacuation after a nuclear accident: Critical reviews of past nuclear accidents and proposal for future planning. Environment international, (148), 106379. https://doi.org/10.1016/j.envint.2021.106379
  • Batur, M., Alkan, R. M. (2023). What can we learn from past nuclear accidents? A comparative assessment of emergency response to accidents at the Three Mile Island, Chernobyl, and Fukushima Nuclear Power Plants. Advanced Land Management, 3(2), 76-89. https://publish.mersin.edu.tr/index.php/alm/article/view/1075
  • Hasegawa, A., Ohira, T., Maeda, M., Yasumura, S., Tanigawa, K. (2016). Emergency responses and health consequences after the Fukushima accident; evacuation and relocation. Clinical Oncology, 28(4), 237-244. https://doi.org/10.1016/j.clon.2016.01.002
  • Oka, Y. (2022). Risks and benefits of evacuation in TEPCO's Fukushima Daiichi nuclear power station accident. Progress in Nuclear Energy, 148, 104222. https://doi.org/10.1016/j.pnucene.2022.104222
  • Sarı, S. & Türk, T. (2021). An investigation of urban development with geographical information systems: 100-year change of Sivas City, Turkey. International Journal of Engineering and Geosciences, 6(1), 51-63.
  • Sohrabi, M., Ghasemi, M., Amrollahi, R., Khamooshi, C., Parsouzi, Z. (2013). Assessment of environmental public exposure from a hypothetical nuclear accident for Unit-1 Bushehr nuclear power plant. Radiation and environmental biophysics, 52, 235-244. https://doi.org/10.1007/s00411-013-0456-y
  • Zhu, Y., Guo, J., Nie, C., Zhou, Y. (2014). Simulation and dose analysis of a hypothetical accident in Sanmen nuclear power plant. Annals of Nuclear Energy, 65, 207-213. https://doi.org/10.1016/j.anucene.2013.11.016
  • Ramana, M. V., Nayyar, A. H., Schoeppner, M. (2016). Nuclear High-level Waste Tank Explosions: Potential Causes and Impacts of a Hypothetical Accident at India's Kalpakkam Reprocessing Plant. Science & Global Security, 24(3), 174-203. https://doi.org/10.1080/08929882.2016.1237661
  • Batur, M., Alkan, R. M., Karaman, H., Ozener, H. (2024). Recommendations for Protective Actions Based on Projected Public Health Risks Following a Postulated Nuclear Power Plant Accident. Malaysian Journal of Fundamental and Applied Sciences, 20(4), 923-938. https://doi.org/10.11113/mjfas.v20n4.3561
  • Mohammed Saeed, I. M., Saleh, M. A. M., Hashim, S., Hama, Y. M. S., Hamza, K., Al-Shatri, S. H. (2020). The radiological assessment, hazard evaluation, and spatial distribution for a hypothetical nuclear power plant accident at Baiji potential site. Environmental Sciences Europe, 32, 1-12. https://doi.org/10.1186/s12302-020-0288-8
  • Murray-Tuite, P., Wolshon, B. (2013). Evacuation transportation modeling: An overview of research, development, and practice. Transportation Research Part C: Emerging Technologies, 27, 25-45. https://doi.org/10.1016/j.trc.2012.11.005
  • Park, S., Sohn, S., Jae, M. (2021). Cohort-based evacuation time estimation using TSIS-CORSIM. Nuclear Engineering and Technology, 53(6), 1979-1990. https://doi.org/10.1016/j.net.2020.11.028
  • Herrera, N., Smith, T., Parr, S. A., Wolshon, B. (2019). Effect of trip generation time on evacuation time estimates. Transportation research record, 2673(11), 101-113. https://doi.org/10.1177/0361198119850793
  • Hsu, Y. T., Peeta, S. (2015). Clearance time estimation for incorporating evacuation risk in routing strategies for evacuation operations. Networks and Spatial Economics, 15, 743-764. https://doi.org/10.1007/s11067-013-9195-5
  • Parr, S. A., Herrera, N., Wolshon, B., Smith, T. (2020). Effect of manual traffic control on evacuation time estimates. Transportation research record, 2674(9), 809-819. https://doi.org/10.1177/0361198120932165
  • Howard, E. E., Pasquini, L., Arbib, C., Di Marco, A., Clementini, E. (2021). Definition of an Enriched GIS Network for Evacuation Planning. In GISTAM, 241-252. https://doi.org/10.5220/0010452302410252
  • Manfré, L. A., Cruz, B. B., Quintanilha, J. A. (2020). Urban settlements and road network analysis on the surrounding area of the Almirante Alvaro Alberto Nuclear Complex, Angra dos Reis, Brazil. Applied spatial analysis and policy, 13, 209-221. https://doi.org/10.1007/s12061-019-09299-2
  • Hasnat, M. M., Islam, M. R., Hadiuzzaman, M. (2018). Emergency response during disastrous situation in densely populated urban areas: a gis based approach. Geographia Technica, 13(2), https://doi.org/10.21163/GT_2018.132.06
  • Maqbool, A., Usmani, Z., Afzal, F., Razia, A. (2020). Disaster mitigation in Urban Pakistan using agent based modeling with GIS. ISPRS International Journal of Geo-Information, 9(4), 203. https://doi.org/10.3390/ijgi9040203
  • Hwang, Y., Heo, G. (2021). Development of a radiological emergency evacuation model using agent-based modeling. Nuclear Engineering and Technology, 53(7), 2195-2206. https://doi.org/10.1016/j.net.2021.01.007
  • Zhang, H., Zhao, Q., Cheng, Z., Liu, L., Su, Y. (2021). Dynamic path optimization with real‐time information for emergency evacuation. Mathematical Problems in Engineering, 2021(1), 3017607. https://doi.org/10.1155/2021/3017607
  • Zeng, M. H., Wang, M., Chen, Y., Yang, Z. (2021). Dynamic evacuation optimization model based on conflict-eliminating cell transmission and split delivery vehicle routing. Safety science, 137, 105166. https://doi.org/10.1016/j.ssci.2021.105166
  • Turcanu, C., Sala, R., Perko, T., Abelshausen, B., Oltra, C., Tomkiv, Y., Zeleznik, N. (2021). How would citizens react to official advice in a nuclear emergency? Insights from research in three European countries. Journal of Contingencies and Crisis Management, 29(2), 143-169. https://doi.org/10.1111/1468-5973.12327
  • Fei, L., Chunhua, C., Fang, R., Yuan, C., Jingxian, Z., Jianye, W. (2023). Influence of human factors on emergency evacuation efficiency of nuclear power plant accident. Journal of Radiation Research and Radiation Processing, 41(4), 40602. 10.11889/j.1000-3436.2022-0128
  • Ma, Y., Xu, W., Qin, L., Zhao, X. (2019). Site selection models in natural disaster shelters: A review. Sustainability, 11(2), 399. https://doi.org/10.3390/su11020399
  • Şentürk, E. & Erener, A. (2017). Determination of temporary shelter areas in natural disasters by gis: A case study, Gölcük/Turkey. International Journal of Engineering and Geosciences, 2(3), 84-90.
  • Wigati, S. S., Sopha, B. M., Asih, A. M. S., Sutanta, H. (2023). Geographic information system based suitable temporary shelter location for Mount Merapi eruption. Sustainability, 15(3), 2073. https://doi.org/10.3390/su15032073
  • Bera, S., Gnyawali, K., Dahal, K., Melo, R., Li-Juan, M., Guru, B., Ramana, G. V. (2023). Assessment of shelter location-allocation for multi-hazard emergency evacuation. International Journal of Disaster Risk Reduction, 84, 103435. https://doi.org/10.1016/j.ijdrr.2022.103435
  • Ozkan, B., Mete, S., Çelik, E., Özceylan, E. (2019). GIS-based maximum covering location model in times of disasters: the case of tunceli. Beykoz Akademi Dergisi, 100-111. https://doi.org/10.14514/BYK.m.26515393.2019.sp/100-111
  • Sotelo-Salas, C., Monardes-Concha, C. A., Perez-Galarce, F., Santa Gonzales, R. (2024). A multi-objective optimization model for planning emergency shelters after a tsunami. Socio-Economic Planning Sciences, 93, 101909. https://doi.org/10.1016/j.seps.2024.101909
  • Zhang, P., Zhang, H., Guo, D. (2015, November). Evacuation shelter and route selection based on multi-objective optimization approach. In Proceedings of the 1st ACM SIGSPATIAL International Workshop on the Use of GIS in Emergency Management, 1-5. https://doi.org/10.1145/2835596.2835598
  • Hallak, J., Koyuncu, M., Miç, P. (2019). Determining shelter locations in conflict areas by multiobjective modeling: A case study in northern Syria. International journal of disaster risk reduction, 38, 101202. https://doi.org/10.1016/j.ijdrr.2019.101202
  • Perez-Galarce, F., Canales, L. J., Vergara, C., Candia-Vejar, A. (2017). An optimization model for the location of disaster refuges. Socio-Economic Planning Sciences, 59, 56-66. https://doi.org/10.1016/j.seps.2016.12.001
  • Kınay, O. B., Kara, B. Y., Saldanha-da-Gama, F., Correia, I. (2018). Modeling the shelter site location problem using chance constraints: A case study for Istanbul. European Journal of Operational Research, 270(1), 132-145. https://doi.org/10.1016/j.ejor.2018.03.006
  • Eriskin, L., Karatas, M. (2022). Applying robust optimization to the shelter location–allocation problem: a case study for Istanbul. Annals of Operations Research, 339, 1589-1635. https://doi.org/10.1007/s10479-022-04627-1
  • Gu, J., Zhou, Y., Das, A., Moon, I., Lee, G. M. (2018). Medical relief shelter location problem with patient severity under a limited relief budget. Computers & Industrial Engineering, 125, 720-728. https://doi.org/10.1016/j.cie.2018.03.027
  • Zhu, J., Li, W., Li, H., Wu, Q., Zhang, L. (2017). A novel swarm intelligence algorithm for the evacuation routing optimization problem. Computational complexity, 1(1), 2.
  • Salam, M. A., Khan, S. A. (2020). Lessons from the humanitarian disaster logistics management: A case study of the earthquake in Haiti. Benchmarking: An International Journal, 27(4), 1455-1473. https://doi.org/10.1108/BIJ-04-2019-0165
  • Caunhye, A. M., Nie, X., Pokharel, S. (2012). Optimization models in emergency logistics: a literature review. Socio-Economic Planning Sciences, 46(1), 4-13. https://doi.org/10.1016/j.seps.2011.04.004
  • Boonmee, C., Arimura, M., Asada, T. (2017). Facility location optimization model for emergency humanitarian logistics. International journal of disaster risk reduction, 24, 485-498. https://doi.org/10.1016/j.ijdrr.2017.01.017
  • Yang, W., Caunhye, A. M., Zhuo, M., Wang, Q. (2024). Integrated planning of emergency supply pre-positioning and victim evacuation. Socio-Economic Planning Sciences, 95, 101965. https://doi.org/10.1016/j.seps.2024.101965
  • Ozbay, E., Çavuş, Ö., Kara, B. Y. (2019). Shelter site location under multi-hazard scenarios. Computers & operations research, 106, 102-118. https://doi.org/10.1016/j.cor.2019.02.008
  • Praneetpholkrang, P., Huynh, V. N. (2020). Shelter site selection and allocation model for efficient response to humanitarian relief logistics. In Dynamics in Logistics: Proceedings of the 7th International Conference LDIC 2020, Bremen, Germany, 309-318. Springer International Publishing. https://doi.org/10.1007/978-3-030-44783-0_30
  • Kanoun, I., Chabchoub, H., Aouni, B. (2010). Goal programming model for fire and emergency service facilities site selection. INFOR: Information Systems and Operational Research, 48(3), 143-153. https://doi.org/10.3138/infor.48.3.143
  • Gormez, N., Koksalan, M., Salman, F. S. (2011). Locating disaster response facilities in Istanbul. Journal of the operational research society, 62(7), 1239-1252. https://doi.org/10.1057/jors.2010.67
  • Xu, W., Zhao, X., Ma, Y., Li, Y., Qin, L., Wang, Y., Du, J. (2018). A multi-objective optimization based method for evaluating earthquake shelter location–allocation. Geomatics, Natural Hazards and Risk, 9(1), 662-677. https://doi.org/10.1080/19475705.2018.1470114
  • Barzinpour, F., Esmaeili, V. (2014). A multi-objective relief chain location distribution model for urban disaster management. The International Journal of Advanced Manufacturing Technology, 70, 1291-1302. https://doi.org/10.1007/s00170-013-5379-x
  • Burkart, C., Nolz, P. C., Gutjahr, W. J. (2017). Modelling beneficiaries’ choice in disaster relief logistics. Annals of Operations Research, 256, 41-61. https://doi.org/10.1007/s10479-015-2097-9
  • Marler, R. T., Arora, J. S. (2010). The weighted sum method for multi-objective optimization: new insights. Structural and multidisciplinary optimization, 41, 853-862. https://doi.org/10.1007/s00158-009-0460-7
  • Mamei, M., Bicocchi, N., Lippi, M., Mariani, S., Zambonelli, F. (2019). Evaluating origin–destination matrices obtained from CDR data. Sensors, 19(20), 4470. https://doi.org/10.3390/s19204470
  • Urbanik, II. T. (2000). Evacuation time estimates for nuclear power plants. Journal of Hazardous Materials, 75(2-3), 165-180. https://doi.org/10.1016/S0304-3894(00)00178-3
  • Zhang, X., Liu, C. A. (2023). Model averaging prediction by K-fold cross-validation. Journal of Econometrics, 235(1), 280-301. https://doi.org/10.1016/j.jeconom.2022.04.007
  • Kyriakides, K. A. (2023). The Akkuyu Nuclear Power Plant in Turkey: Some Causes for Concern. Journal of Balkan and Near Eastern Studies, 25(3), 340-377. https://doi.org/10.1080/19448953.2022.2143855
  • Unel, F. B., Kusak, L., & Yakar, M. (2023). GeoValueIndex map of public property assets generating via Analytic Hierarchy Process and Geographic Information System for Mass Appraisal: GeoValueIndex. Aestimum, 82, 51-69
  • Güven, O., Yıldırım, Ümit ., Güler, C., & Kurt, M. A. (2024). Land use and land cover classes affected by the possible sea level rise in Mersin city center (Türkiye). Advanced GIS, 4(1), 15–23. Retrieved from https://publish.mersin.edu.tr/index.php/agis/article/view/1348
  • Topaloglu, R. H. (2022). Investigation of Land Use/Land Cover change in Mersin using geographical object-based image analysis (GEOBIA). Advanced Remote Sensing, 2(2), 40–46. Retrieved from https://publish.mersin.edu.tr/index.php/arsej/article/view/247 Yilmaz, C. B., Sevimli, M. F., Demir, F., Yakar, M. (2021). Trend analysis of temperature and precipitation in Mediterranean region. Advanced GIS, 1(1), 15-21. Retrieved from https://publish.merisn.edu.tr/index.php/agis/article/view/60
  • Balcı, D. (2022). Researching the use of infrastructure in land management. Advanced GIS, 2(1), 18–23. Retrieved from https://publish.mersin.edu.tr/index.php/agis/article/view/250
  • General Directorate of Highways. The Republic of Turkey General Directorate of Highways. Republic of Turkey, www.kgm.gov.tr. Accessed on September 2024.
  • Bijaber, N., Rochdi, A., Yessef, M., El Yacoubi, H. (2024). Mapping the structural vulnerability to drought in Morocco. International Journal of Engineering and Geosciences, 9(2), 264-280. https://doi.org/10.26833/ijeg.1404507

Multi-dimensional optimization of nuclear emergency shelters: balancing capacity, evacuation efficiency, and supply accessibility

Year 2025, Volume: 10 Issue: 2, 244 - 261
https://doi.org/10.26833/ijeg.1596244

Abstract

Effective shelter location-allocation is critical in nuclear emergencies to ensure rapid, safe evacuation and resource access for affected populations. This study presents a multi-dimensional optimization model for shelter allocation within humanitarian logistics, balancing evacuation time, supply accessibility, and shelter capacity. Using Geographic Information Systems (GIS) and Multi-Criteria Decision Analysis (MCDA), the model optimizes trade-offs among competing objectives. The first objective minimizes evacuation time, the second ensures adequate supply access, and the third prevents shelter overcrowding. Validated through k-fold cross-validation, the model reveals spatial biases: evacuees often cluster in nearby shelters, leading to overcrowding in dense areas and underuse in others. This analysis suggests adding flexible shelters in high-density zones to enhance response efficiency. Overall, the research supports more balanced shelter allocations in nuclear emergencies, improving both immediate and long-term disaster response strategies for affected populations

References

  • Ohba, T., Tanigawa, K., Liutsko, L. (2021). Evacuation after a nuclear accident: Critical reviews of past nuclear accidents and proposal for future planning. Environment international, (148), 106379. https://doi.org/10.1016/j.envint.2021.106379
  • Batur, M., Alkan, R. M. (2023). What can we learn from past nuclear accidents? A comparative assessment of emergency response to accidents at the Three Mile Island, Chernobyl, and Fukushima Nuclear Power Plants. Advanced Land Management, 3(2), 76-89. https://publish.mersin.edu.tr/index.php/alm/article/view/1075
  • Hasegawa, A., Ohira, T., Maeda, M., Yasumura, S., Tanigawa, K. (2016). Emergency responses and health consequences after the Fukushima accident; evacuation and relocation. Clinical Oncology, 28(4), 237-244. https://doi.org/10.1016/j.clon.2016.01.002
  • Oka, Y. (2022). Risks and benefits of evacuation in TEPCO's Fukushima Daiichi nuclear power station accident. Progress in Nuclear Energy, 148, 104222. https://doi.org/10.1016/j.pnucene.2022.104222
  • Sarı, S. & Türk, T. (2021). An investigation of urban development with geographical information systems: 100-year change of Sivas City, Turkey. International Journal of Engineering and Geosciences, 6(1), 51-63.
  • Sohrabi, M., Ghasemi, M., Amrollahi, R., Khamooshi, C., Parsouzi, Z. (2013). Assessment of environmental public exposure from a hypothetical nuclear accident for Unit-1 Bushehr nuclear power plant. Radiation and environmental biophysics, 52, 235-244. https://doi.org/10.1007/s00411-013-0456-y
  • Zhu, Y., Guo, J., Nie, C., Zhou, Y. (2014). Simulation and dose analysis of a hypothetical accident in Sanmen nuclear power plant. Annals of Nuclear Energy, 65, 207-213. https://doi.org/10.1016/j.anucene.2013.11.016
  • Ramana, M. V., Nayyar, A. H., Schoeppner, M. (2016). Nuclear High-level Waste Tank Explosions: Potential Causes and Impacts of a Hypothetical Accident at India's Kalpakkam Reprocessing Plant. Science & Global Security, 24(3), 174-203. https://doi.org/10.1080/08929882.2016.1237661
  • Batur, M., Alkan, R. M., Karaman, H., Ozener, H. (2024). Recommendations for Protective Actions Based on Projected Public Health Risks Following a Postulated Nuclear Power Plant Accident. Malaysian Journal of Fundamental and Applied Sciences, 20(4), 923-938. https://doi.org/10.11113/mjfas.v20n4.3561
  • Mohammed Saeed, I. M., Saleh, M. A. M., Hashim, S., Hama, Y. M. S., Hamza, K., Al-Shatri, S. H. (2020). The radiological assessment, hazard evaluation, and spatial distribution for a hypothetical nuclear power plant accident at Baiji potential site. Environmental Sciences Europe, 32, 1-12. https://doi.org/10.1186/s12302-020-0288-8
  • Murray-Tuite, P., Wolshon, B. (2013). Evacuation transportation modeling: An overview of research, development, and practice. Transportation Research Part C: Emerging Technologies, 27, 25-45. https://doi.org/10.1016/j.trc.2012.11.005
  • Park, S., Sohn, S., Jae, M. (2021). Cohort-based evacuation time estimation using TSIS-CORSIM. Nuclear Engineering and Technology, 53(6), 1979-1990. https://doi.org/10.1016/j.net.2020.11.028
  • Herrera, N., Smith, T., Parr, S. A., Wolshon, B. (2019). Effect of trip generation time on evacuation time estimates. Transportation research record, 2673(11), 101-113. https://doi.org/10.1177/0361198119850793
  • Hsu, Y. T., Peeta, S. (2015). Clearance time estimation for incorporating evacuation risk in routing strategies for evacuation operations. Networks and Spatial Economics, 15, 743-764. https://doi.org/10.1007/s11067-013-9195-5
  • Parr, S. A., Herrera, N., Wolshon, B., Smith, T. (2020). Effect of manual traffic control on evacuation time estimates. Transportation research record, 2674(9), 809-819. https://doi.org/10.1177/0361198120932165
  • Howard, E. E., Pasquini, L., Arbib, C., Di Marco, A., Clementini, E. (2021). Definition of an Enriched GIS Network for Evacuation Planning. In GISTAM, 241-252. https://doi.org/10.5220/0010452302410252
  • Manfré, L. A., Cruz, B. B., Quintanilha, J. A. (2020). Urban settlements and road network analysis on the surrounding area of the Almirante Alvaro Alberto Nuclear Complex, Angra dos Reis, Brazil. Applied spatial analysis and policy, 13, 209-221. https://doi.org/10.1007/s12061-019-09299-2
  • Hasnat, M. M., Islam, M. R., Hadiuzzaman, M. (2018). Emergency response during disastrous situation in densely populated urban areas: a gis based approach. Geographia Technica, 13(2), https://doi.org/10.21163/GT_2018.132.06
  • Maqbool, A., Usmani, Z., Afzal, F., Razia, A. (2020). Disaster mitigation in Urban Pakistan using agent based modeling with GIS. ISPRS International Journal of Geo-Information, 9(4), 203. https://doi.org/10.3390/ijgi9040203
  • Hwang, Y., Heo, G. (2021). Development of a radiological emergency evacuation model using agent-based modeling. Nuclear Engineering and Technology, 53(7), 2195-2206. https://doi.org/10.1016/j.net.2021.01.007
  • Zhang, H., Zhao, Q., Cheng, Z., Liu, L., Su, Y. (2021). Dynamic path optimization with real‐time information for emergency evacuation. Mathematical Problems in Engineering, 2021(1), 3017607. https://doi.org/10.1155/2021/3017607
  • Zeng, M. H., Wang, M., Chen, Y., Yang, Z. (2021). Dynamic evacuation optimization model based on conflict-eliminating cell transmission and split delivery vehicle routing. Safety science, 137, 105166. https://doi.org/10.1016/j.ssci.2021.105166
  • Turcanu, C., Sala, R., Perko, T., Abelshausen, B., Oltra, C., Tomkiv, Y., Zeleznik, N. (2021). How would citizens react to official advice in a nuclear emergency? Insights from research in three European countries. Journal of Contingencies and Crisis Management, 29(2), 143-169. https://doi.org/10.1111/1468-5973.12327
  • Fei, L., Chunhua, C., Fang, R., Yuan, C., Jingxian, Z., Jianye, W. (2023). Influence of human factors on emergency evacuation efficiency of nuclear power plant accident. Journal of Radiation Research and Radiation Processing, 41(4), 40602. 10.11889/j.1000-3436.2022-0128
  • Ma, Y., Xu, W., Qin, L., Zhao, X. (2019). Site selection models in natural disaster shelters: A review. Sustainability, 11(2), 399. https://doi.org/10.3390/su11020399
  • Şentürk, E. & Erener, A. (2017). Determination of temporary shelter areas in natural disasters by gis: A case study, Gölcük/Turkey. International Journal of Engineering and Geosciences, 2(3), 84-90.
  • Wigati, S. S., Sopha, B. M., Asih, A. M. S., Sutanta, H. (2023). Geographic information system based suitable temporary shelter location for Mount Merapi eruption. Sustainability, 15(3), 2073. https://doi.org/10.3390/su15032073
  • Bera, S., Gnyawali, K., Dahal, K., Melo, R., Li-Juan, M., Guru, B., Ramana, G. V. (2023). Assessment of shelter location-allocation for multi-hazard emergency evacuation. International Journal of Disaster Risk Reduction, 84, 103435. https://doi.org/10.1016/j.ijdrr.2022.103435
  • Ozkan, B., Mete, S., Çelik, E., Özceylan, E. (2019). GIS-based maximum covering location model in times of disasters: the case of tunceli. Beykoz Akademi Dergisi, 100-111. https://doi.org/10.14514/BYK.m.26515393.2019.sp/100-111
  • Sotelo-Salas, C., Monardes-Concha, C. A., Perez-Galarce, F., Santa Gonzales, R. (2024). A multi-objective optimization model for planning emergency shelters after a tsunami. Socio-Economic Planning Sciences, 93, 101909. https://doi.org/10.1016/j.seps.2024.101909
  • Zhang, P., Zhang, H., Guo, D. (2015, November). Evacuation shelter and route selection based on multi-objective optimization approach. In Proceedings of the 1st ACM SIGSPATIAL International Workshop on the Use of GIS in Emergency Management, 1-5. https://doi.org/10.1145/2835596.2835598
  • Hallak, J., Koyuncu, M., Miç, P. (2019). Determining shelter locations in conflict areas by multiobjective modeling: A case study in northern Syria. International journal of disaster risk reduction, 38, 101202. https://doi.org/10.1016/j.ijdrr.2019.101202
  • Perez-Galarce, F., Canales, L. J., Vergara, C., Candia-Vejar, A. (2017). An optimization model for the location of disaster refuges. Socio-Economic Planning Sciences, 59, 56-66. https://doi.org/10.1016/j.seps.2016.12.001
  • Kınay, O. B., Kara, B. Y., Saldanha-da-Gama, F., Correia, I. (2018). Modeling the shelter site location problem using chance constraints: A case study for Istanbul. European Journal of Operational Research, 270(1), 132-145. https://doi.org/10.1016/j.ejor.2018.03.006
  • Eriskin, L., Karatas, M. (2022). Applying robust optimization to the shelter location–allocation problem: a case study for Istanbul. Annals of Operations Research, 339, 1589-1635. https://doi.org/10.1007/s10479-022-04627-1
  • Gu, J., Zhou, Y., Das, A., Moon, I., Lee, G. M. (2018). Medical relief shelter location problem with patient severity under a limited relief budget. Computers & Industrial Engineering, 125, 720-728. https://doi.org/10.1016/j.cie.2018.03.027
  • Zhu, J., Li, W., Li, H., Wu, Q., Zhang, L. (2017). A novel swarm intelligence algorithm for the evacuation routing optimization problem. Computational complexity, 1(1), 2.
  • Salam, M. A., Khan, S. A. (2020). Lessons from the humanitarian disaster logistics management: A case study of the earthquake in Haiti. Benchmarking: An International Journal, 27(4), 1455-1473. https://doi.org/10.1108/BIJ-04-2019-0165
  • Caunhye, A. M., Nie, X., Pokharel, S. (2012). Optimization models in emergency logistics: a literature review. Socio-Economic Planning Sciences, 46(1), 4-13. https://doi.org/10.1016/j.seps.2011.04.004
  • Boonmee, C., Arimura, M., Asada, T. (2017). Facility location optimization model for emergency humanitarian logistics. International journal of disaster risk reduction, 24, 485-498. https://doi.org/10.1016/j.ijdrr.2017.01.017
  • Yang, W., Caunhye, A. M., Zhuo, M., Wang, Q. (2024). Integrated planning of emergency supply pre-positioning and victim evacuation. Socio-Economic Planning Sciences, 95, 101965. https://doi.org/10.1016/j.seps.2024.101965
  • Ozbay, E., Çavuş, Ö., Kara, B. Y. (2019). Shelter site location under multi-hazard scenarios. Computers & operations research, 106, 102-118. https://doi.org/10.1016/j.cor.2019.02.008
  • Praneetpholkrang, P., Huynh, V. N. (2020). Shelter site selection and allocation model for efficient response to humanitarian relief logistics. In Dynamics in Logistics: Proceedings of the 7th International Conference LDIC 2020, Bremen, Germany, 309-318. Springer International Publishing. https://doi.org/10.1007/978-3-030-44783-0_30
  • Kanoun, I., Chabchoub, H., Aouni, B. (2010). Goal programming model for fire and emergency service facilities site selection. INFOR: Information Systems and Operational Research, 48(3), 143-153. https://doi.org/10.3138/infor.48.3.143
  • Gormez, N., Koksalan, M., Salman, F. S. (2011). Locating disaster response facilities in Istanbul. Journal of the operational research society, 62(7), 1239-1252. https://doi.org/10.1057/jors.2010.67
  • Xu, W., Zhao, X., Ma, Y., Li, Y., Qin, L., Wang, Y., Du, J. (2018). A multi-objective optimization based method for evaluating earthquake shelter location–allocation. Geomatics, Natural Hazards and Risk, 9(1), 662-677. https://doi.org/10.1080/19475705.2018.1470114
  • Barzinpour, F., Esmaeili, V. (2014). A multi-objective relief chain location distribution model for urban disaster management. The International Journal of Advanced Manufacturing Technology, 70, 1291-1302. https://doi.org/10.1007/s00170-013-5379-x
  • Burkart, C., Nolz, P. C., Gutjahr, W. J. (2017). Modelling beneficiaries’ choice in disaster relief logistics. Annals of Operations Research, 256, 41-61. https://doi.org/10.1007/s10479-015-2097-9
  • Marler, R. T., Arora, J. S. (2010). The weighted sum method for multi-objective optimization: new insights. Structural and multidisciplinary optimization, 41, 853-862. https://doi.org/10.1007/s00158-009-0460-7
  • Mamei, M., Bicocchi, N., Lippi, M., Mariani, S., Zambonelli, F. (2019). Evaluating origin–destination matrices obtained from CDR data. Sensors, 19(20), 4470. https://doi.org/10.3390/s19204470
  • Urbanik, II. T. (2000). Evacuation time estimates for nuclear power plants. Journal of Hazardous Materials, 75(2-3), 165-180. https://doi.org/10.1016/S0304-3894(00)00178-3
  • Zhang, X., Liu, C. A. (2023). Model averaging prediction by K-fold cross-validation. Journal of Econometrics, 235(1), 280-301. https://doi.org/10.1016/j.jeconom.2022.04.007
  • Kyriakides, K. A. (2023). The Akkuyu Nuclear Power Plant in Turkey: Some Causes for Concern. Journal of Balkan and Near Eastern Studies, 25(3), 340-377. https://doi.org/10.1080/19448953.2022.2143855
  • Unel, F. B., Kusak, L., & Yakar, M. (2023). GeoValueIndex map of public property assets generating via Analytic Hierarchy Process and Geographic Information System for Mass Appraisal: GeoValueIndex. Aestimum, 82, 51-69
  • Güven, O., Yıldırım, Ümit ., Güler, C., & Kurt, M. A. (2024). Land use and land cover classes affected by the possible sea level rise in Mersin city center (Türkiye). Advanced GIS, 4(1), 15–23. Retrieved from https://publish.mersin.edu.tr/index.php/agis/article/view/1348
  • Topaloglu, R. H. (2022). Investigation of Land Use/Land Cover change in Mersin using geographical object-based image analysis (GEOBIA). Advanced Remote Sensing, 2(2), 40–46. Retrieved from https://publish.mersin.edu.tr/index.php/arsej/article/view/247 Yilmaz, C. B., Sevimli, M. F., Demir, F., Yakar, M. (2021). Trend analysis of temperature and precipitation in Mediterranean region. Advanced GIS, 1(1), 15-21. Retrieved from https://publish.merisn.edu.tr/index.php/agis/article/view/60
  • Balcı, D. (2022). Researching the use of infrastructure in land management. Advanced GIS, 2(1), 18–23. Retrieved from https://publish.mersin.edu.tr/index.php/agis/article/view/250
  • General Directorate of Highways. The Republic of Turkey General Directorate of Highways. Republic of Turkey, www.kgm.gov.tr. Accessed on September 2024.
  • Bijaber, N., Rochdi, A., Yessef, M., El Yacoubi, H. (2024). Mapping the structural vulnerability to drought in Morocco. International Journal of Engineering and Geosciences, 9(2), 264-280. https://doi.org/10.26833/ijeg.1404507
There are 59 citations in total.

Details

Primary Language English
Subjects Land Management, Geographical Information Systems (GIS) in Planning
Journal Section Research Article
Authors

Maryna Batur 0000-0001-9284-8858

Reha Metin Alkan 0000-0002-1981-9783

Himmet Karaman 0000-0003-4923-3561

Haluk Özener 0000-0003-2531-3030

Early Pub Date January 25, 2025
Publication Date
Submission Date December 4, 2024
Acceptance Date January 17, 2025
Published in Issue Year 2025 Volume: 10 Issue: 2

Cite

APA Batur, M., Alkan, R. M., Karaman, H., Özener, H. (2025). Multi-dimensional optimization of nuclear emergency shelters: balancing capacity, evacuation efficiency, and supply accessibility. International Journal of Engineering and Geosciences, 10(2), 244-261. https://doi.org/10.26833/ijeg.1596244
AMA Batur M, Alkan RM, Karaman H, Özener H. Multi-dimensional optimization of nuclear emergency shelters: balancing capacity, evacuation efficiency, and supply accessibility. IJEG. January 2025;10(2):244-261. doi:10.26833/ijeg.1596244
Chicago Batur, Maryna, Reha Metin Alkan, Himmet Karaman, and Haluk Özener. “Multi-Dimensional Optimization of Nuclear Emergency Shelters: Balancing Capacity, Evacuation Efficiency, and Supply Accessibility”. International Journal of Engineering and Geosciences 10, no. 2 (January 2025): 244-61. https://doi.org/10.26833/ijeg.1596244.
EndNote Batur M, Alkan RM, Karaman H, Özener H (January 1, 2025) Multi-dimensional optimization of nuclear emergency shelters: balancing capacity, evacuation efficiency, and supply accessibility. International Journal of Engineering and Geosciences 10 2 244–261.
IEEE M. Batur, R. M. Alkan, H. Karaman, and H. Özener, “Multi-dimensional optimization of nuclear emergency shelters: balancing capacity, evacuation efficiency, and supply accessibility”, IJEG, vol. 10, no. 2, pp. 244–261, 2025, doi: 10.26833/ijeg.1596244.
ISNAD Batur, Maryna et al. “Multi-Dimensional Optimization of Nuclear Emergency Shelters: Balancing Capacity, Evacuation Efficiency, and Supply Accessibility”. International Journal of Engineering and Geosciences 10/2 (January 2025), 244-261. https://doi.org/10.26833/ijeg.1596244.
JAMA Batur M, Alkan RM, Karaman H, Özener H. Multi-dimensional optimization of nuclear emergency shelters: balancing capacity, evacuation efficiency, and supply accessibility. IJEG. 2025;10:244–261.
MLA Batur, Maryna et al. “Multi-Dimensional Optimization of Nuclear Emergency Shelters: Balancing Capacity, Evacuation Efficiency, and Supply Accessibility”. International Journal of Engineering and Geosciences, vol. 10, no. 2, 2025, pp. 244-61, doi:10.26833/ijeg.1596244.
Vancouver Batur M, Alkan RM, Karaman H, Özener H. Multi-dimensional optimization of nuclear emergency shelters: balancing capacity, evacuation efficiency, and supply accessibility. IJEG. 2025;10(2):244-61.