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http://bura.brunel.ac.uk/handle/2438/24921| Title: | Camp Location Selection in Humanitarian Logistics: A Multiobjective Simulation Optimization Approach |
| Authors: | Xue, Y Li, M Arabnejad, H Suleimenova, D Jahani, A C. Geiger, B Wang, Z Liu, X Groen, D |
| Keywords: | Facility location problem;Multiobjective optimization;Simulation;Evolutionary algorithms |
| Issue Date: | 15-Jun-2022 |
| Publisher: | Springer, Cham |
| Citation: | Xue, Y. et al. (2022) 'Camp Location Selection in Humanitarian Logistics: A Multiobjective Simulation Optimization Approach', 22nd International Conference on Computational Science (ICCS 2022), 13352, pp. 497 - 504. doi:10.1007/978-3-031-08757-8_42. |
| Abstract: | In the context of humanitarian support for forcibly displaced persons, camps play an important role in protecting people and ensuring their survival and health. A challenge in this regard is to find optimal locations for establishing a new asylum-seeker/unrecognized refugee or IDPs (internally displaced persons) camp. In this paper we formulate this problem as an instantiation of the well-known facility location problem (FLP) with three objectives to be optimized. In particular, we show that AI techniques and migration simulations can be used to provide decision support on camp placement. |
| Description: | Acknowledgements: This work is supported by the ITFLOWS and HiDALGO projects, which have received funding from the European Union Horizon 2020 research and innovation programme under grant agreement nos 882986 and 824115. The authors are grateful to Prof. Simon J E Taylor and Dr. Anastasia Anagnostou for their constructive discussions on this work. |
| URI: | https://bura.brunel.ac.uk/handle/2438/24921 |
| DOI: | http://doi.org/10.1007/978-3-031-08757-8_42 |
| ISBN: | 978-3-031-08757-8 |
| Appears in Collections: | Dept of Computer Science Research Papers |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| FullText.pdf | © 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG | 587.17 kB | Adobe PDF | View/Open |
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