Abstract
In times of disasters, accessing to shelters by the victims is a vital task in humanitarian logistics.
One of the humanitarian logistics challenges is the difficulty involved in effectively
coordinating large numbers of victims. Especially, the lack of spatial information involved in
the rescue and recovery region is an obstacle for efficient planning. In this paper, a geographic
information system (GIS)-based solution approach is developed to manage the assignments of
victims to the shelters in times of disasters. To do so, the capacitated maximize coverage tool
of ArcGIS is used and tested on the case of Tunceli city. As a result, different scenario analyses
are generated under the distance and time restrictions between victims and shelters. Case results
demonstrate the proposed approach’s ability to support efficient and effective disaster
management.
Keywords
Capacitated location-allocation case study disaster management geographic information system maximum covering
References
- Boonmee, C., Arimura, M. & Asada, T. (2017). Facility location optimization model for emergency humanitarian logistics. International Journal of Disaster Risk Reduction, 24, 485–498.
- Dal, M., Öcal, A.D. & Göktepe, D. (2017). Natural disaster of Tunceli province and its environment. Proceedings of 4th International Regional Development Conference, Tunceli (pp. 601–607).
- Doungpan, S., Moryadee, S., U-Tapao, C. & Laokhongthavorn, Z. (2018). Analysis of three emergency medical location models: A case study of Thailand. Proceedings of International Conference on System Science and Engineering (pp. 1–6).
- Fetter, G. & Rakes, T. (2012). Incorporating recycling into post-disaster debris disposal. SocioEconomic Planning Sciences, 46(1), 14–22.
- Haghani, A. (1996). Capacitated maximum covering location models: Formulations and solution procedures. Journal of Advanced Transportation, 30(3), 101–136.
- Hashim, N.M., Shariff, S.S.R. & Deni, S.M. (2017). Capacitated maximal covering location allocation problem during flood disaster. Advanced Science Letters, 23(11), 11545– 11548.
- Onat, O. & Yön, B. (2018). Earthquake risk amplification based on architectural plan irregularity. Proceedings of 2nd International Symposium on Natural Hazards and Disaster Management, Sakarya (pp. 665–674).
- Pan, A.-P. (2011). A constructive genetic algorithm for the P-median location problem of typhoon emergency shelter in China coastal rural areas. Key Engineering Materials, 480-481, 1215–1220.
- Saeidian, B., Mesgari, M.S., Pradhan, B. & Ghodousi, M. (2018). Optimized location-allocation of earthquake relief centers using PSO and ACO, Complemented by GIS, Clustering, and TOPSIS. ISPRS International Journal of Geo-Information, 7(8), 1–25.
- Tavakkoli-Moghaddam, R., Memari, P. & Talebi, E. (2018). A bi-objective location-allocation problem of temporary emergency stations and ambulance routing in a disaster situation. Proceedings of 4th International Conference on Optimization and Applications, Morocco (pp. 1–4).
- Ye, F., Zhao, Q., Xi, M. & Dessouky, M. (2015). Chinese national emergency warehouse location research based on VNS algorithm. Electronic Notes in Discrete Mathematics, 47, 61–68.
- Zhang, M., Zhang, Y., Qiu, Z. & Wu, H. (2019). Two-stage covering location model for airground medical rescue system. Sustainability, 11(12), 3242.
Abstract
References
- Boonmee, C., Arimura, M. & Asada, T. (2017). Facility location optimization model for emergency humanitarian logistics. International Journal of Disaster Risk Reduction, 24, 485–498.
- Dal, M., Öcal, A.D. & Göktepe, D. (2017). Natural disaster of Tunceli province and its environment. Proceedings of 4th International Regional Development Conference, Tunceli (pp. 601–607).
- Doungpan, S., Moryadee, S., U-Tapao, C. & Laokhongthavorn, Z. (2018). Analysis of three emergency medical location models: A case study of Thailand. Proceedings of International Conference on System Science and Engineering (pp. 1–6).
- Fetter, G. & Rakes, T. (2012). Incorporating recycling into post-disaster debris disposal. SocioEconomic Planning Sciences, 46(1), 14–22.
- Haghani, A. (1996). Capacitated maximum covering location models: Formulations and solution procedures. Journal of Advanced Transportation, 30(3), 101–136.
- Hashim, N.M., Shariff, S.S.R. & Deni, S.M. (2017). Capacitated maximal covering location allocation problem during flood disaster. Advanced Science Letters, 23(11), 11545– 11548.
- Onat, O. & Yön, B. (2018). Earthquake risk amplification based on architectural plan irregularity. Proceedings of 2nd International Symposium on Natural Hazards and Disaster Management, Sakarya (pp. 665–674).
- Pan, A.-P. (2011). A constructive genetic algorithm for the P-median location problem of typhoon emergency shelter in China coastal rural areas. Key Engineering Materials, 480-481, 1215–1220.
- Saeidian, B., Mesgari, M.S., Pradhan, B. & Ghodousi, M. (2018). Optimized location-allocation of earthquake relief centers using PSO and ACO, Complemented by GIS, Clustering, and TOPSIS. ISPRS International Journal of Geo-Information, 7(8), 1–25.
- Tavakkoli-Moghaddam, R., Memari, P. & Talebi, E. (2018). A bi-objective location-allocation problem of temporary emergency stations and ambulance routing in a disaster situation. Proceedings of 4th International Conference on Optimization and Applications, Morocco (pp. 1–4).
- Ye, F., Zhao, Q., Xi, M. & Dessouky, M. (2015). Chinese national emergency warehouse location research based on VNS algorithm. Electronic Notes in Discrete Mathematics, 47, 61–68.
- Zhang, M., Zhang, Y., Qiu, Z. & Wu, H. (2019). Two-stage covering location model for airground medical rescue system. Sustainability, 11(12), 3242.
Details
| Primary Language | English |
|---|---|
| Journal Section | Articles |
| Authors | |
| Publication Date | October 1, 2019 |
| Submission Date | August 20, 2019 |
| Acceptance Date | October 1, 2019 |
| Published in Issue | Year 2019 BEYKOZ AKADEMİ 2019 ÖZEL SAYI |
