Simulation of Migration Paths Using Agent-Based Modeling: the Case of Syrian Refugees En Route To Turkey

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The decade-long Syrian civil war has triggered a significant migration wave in the Middle East, with Turkey hosting the largest number of Syrian refugees. Our study introduces an agent-based model (ABM) designed to simulate and predict migration paths in potential future refugee crises. The primary goal is to support aid organizations in planning the delivery of essential aid services during migration movements, offering insights that can be applied to various geographical areas and migration scenarios. While we use the Syrian refugee movement to Turkey as a case study, the model is intended as a flexible tool for analyzing migration patterns in future crises. The proposed ABM considers two characteristics of refugee groups: level of risk sensitivity and level of information. To enhance the model's functionality, we have extended the A* algorithm with a cost metric to calculate the weighted average of distance and risk to a destination point. Our case study examines the crisis in southern Idlib through six scenarios, offering insights into refugee numbers, migration paths, camp occupancy rates, and heat maps of densely populated regions for each scenario. Validation is performed by comparing model outcomes with situation reports and official statements from the relevant period, demonstrating the proposed ABM's potential for adaptation to other migration instances and further analysis under different parameters. © 2024 Elsevier Ltd

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Anahtar kelimeler

Agent-based modeling, Forced migration, Migration paths, Risk sensitivity, Syrian refugees, Turkey, civil war, forced migration, future prospect, migration, refugee, risk assessment, scenario analysis, Turkey, future prospect, civil war, forced migration, risk assessment, Forced migration, scenario analysis, migration, Migration paths, Agent-based modeling, Syrian refugees, refugee, Risk sensitivity

Bilim Dalları

05 social sciences, 01 natural sciences, 0502 economics and business, 0103 physical sciences

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Q1

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2

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Socio-Economic Planning Sciences

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96

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102089

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