A framework for modelling conflict-induced forced migration according to an agent-based approach
Date
2019-12
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Stellenbosch : Stellenbosch University
Abstract
ENGLISH ABSTRACT: Over the course of the past decade, numerous calamities worldwide have led to phrases such as
`refugee' and `undocumented migrant' becoming commonplace in the public discourse. Conflictinduced
displacement and the various challenges it creates have received notable attention. A
particular challenge posed by the management of sudden migration of large groups of people lies in a general inability to predict the scale and dynamics of such movement accurately. This problem is further complicated by the fact that data associated with such migration are largely
incomplete or untrustworthy.
Presently, there is a significant lack of data required to perform strategic, long-term planning
related to current and future conflict crisis situations. One of the most fundamental challenges
faced by researchers and humanitarian aid organisations when addressing forced displacement is an inability to predict the types of movement and the destinations of those who are forcibly displaced. The provision of a reasonably accurate estimation of the number of forcibly displaced people is potentially a critical input for the planning of logistics and management of structures supporting those
eeing violence and persecution.
A framework is proposed in this dissertation for assisting in the development and application of agent-based simulation models for predicting conflict-induced migration. The framework
comprises five phases which encapsulate the formulation, conceptualisation and development of such a model, as well as the associated model execution and documentation. The purpose of the framework is to facilitate the design and development of agent-based models that incorporate the
determinant factors of localised decision making and generate the resulting emergent large-scale
movement patterns of forced migration.
Collaboration with various subject matter experts throughout the development of this framework allowed for significant insight to be gained from the confluence of research in the fields of forced migration, computer simulation and human decision-making processes, which does not presently
appear in the literature. The approach suggested for modelling human decision making is endorsed by knowledge gained from this research confluence, which has been corroborated by expert opinion. To the best of the knowledge of the consulted subject matter experts, no such framework encompassing such a wide variety of factors and implications pertaining to forced migration modelling in the presence of conflict presently exists and, as such, the research has
sparked significant interest in the international research community.
A concept demonstrator is furthermore developed according to the proposed framework in an attempt to demonstrate its usefulness and practicability in the context of conflict-induced migration in Syria. The model concept demonstrator is developed in the AnyLogic simulation
software environment and allows for an animated output visualisation of the state of conflict
pertaining to specified geographic and time scales, with super-imposed agent movement based on
localised decision making when confronted with con
ict. As per the framework, the model concept
demonstrator is subjected to a number of traditional verification and validation techniques which include the calibration of parameters related to the modelling of con
ict, the replication of visualised recorded data, the validation of the relevant agent aggregation, a thorough face
validation and a parameter variation analysis which, ultimately, facilitates the implementation of a graphical user interface. The model concept demonstrator is thereby deemed capable of modelling specified scenarios of con
ict-induced migration when equipped with the correct parameter values, owing to its
exibility. The animation output also allows for easy interpretation of the model output, particularly by parties who are not necessarily scientifically trained.
A framework of this nature naturally presents numerous avenues for future work. By employing machine learning and data mining tools, such follow-up work may, for example, ultimately lead to a framework for assisting in planning and the formulation of logistics strategies in the lieu of
identifying required facilities and resources. Such an enhanced framework may prove invaluable in the accommodation of incoming refugees, internally displaced migrants and undocumented
migrants in different areas, by predicting the population
uctuations in affected areas during
times of conflict, natural disaster, or other forced migration-causing events.
AFRIKAANSE OPSOMMING: Raadpleeg teks vir opsomming
AFRIKAANSE OPSOMMING: Raadpleeg teks vir opsomming
Description
Thesis (PhD)--Stellenbosch University, 2019.
Keywords
Forced migration -- Management, Agent-based simulation, Forced migration, UCTD, Ethnic conflict