Abstract
The success of refugee support operations depends on the ability of humanitarian organizations and governments to deploy aid effectively. These operations require that decisions on resource allocation are made as quickly as possible in order to respond to urgent crises and, by anticipating future developments, remain adequate as the situation evolves. Agent-based modeling and simulation has been used to understand the progression of past refugee crises, as well as a way to predict how new ones will unfold. In this work, we tackle the problem of refugee aid deployment as a variant of the Robust Facility Location Problem (RFLP). We present a serious video game that functions as an interface for an agent-based simulation run with data from past refugee crises. Having obtained good approximate solutions to the RFLP by implementing a game that frames the problem as a puzzle, we adapted its mechanics and interface to correspond to refugee situations. The game is intended to be played by both subject matter experts and the general public, as a way to crowd-source effective courses of action in these situations.
| Original language | English |
|---|---|
| Pages (from-to) | 205-214 |
| Number of pages | 10 |
| Journal | Procedia Computer Science |
| Volume | 108 |
| DOIs | |
| State | Published - 2017 |
| Event | International Conference on Computational Science ICCS 2017 - Zurich, Switzerland Duration: 12 Jun 2017 → 14 Jun 2017 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 16 Peace, Justice and Strong Institutions
Keywords
- Refugees
- modeling
- serious games
- simulation
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