Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/10976
Title: An intelligent multi-agent system using fuzzy analytic hierarchy process and axiomatic design as a decision support method for refugee settlement siting
Authors: Drakaki, M.
Gören, H.G.
Tzionas, P.
Keywords: Decision support method
Intelligent multi-agent system
Refugee crisis
Refugee settlement planning
Analytic hierarchy process
Decision making
Decision support systems
Multi agent systems
Supply chain management
Decision making process
Decision supports
Fuzzy analytic hierarchy process
Humanitarian relief operations
Intelligent multi agent systems
Logistics operations
Multi-criteria decision making
Intelligent agents
Publisher: Springer Verlag
Abstract: Crises and disasters of recent years are complex and occasionally interrelated phenomena, which require complex decision making for effective humanitarian relief operations provision. Moreover, coordination is needed between different humanitarian actors as decision makers. Massive refugee and migrant arrivals in Greece since 2014, mainly a result of a refugee crisis, require complex humanitarian supply chain management and logistics operations. In this paper, refugee settlement site planning decision making process is addressed with an intelligent multi-agent system (MAS) modeling approach. The MAS uses two multi-criteria decision making (MCDM) methods: fuzzy analytic hierarchy process (FAHP) to determine the weights of criteria and fuzzy axiomatic design approach extended with risk factors (RFAD) to rank alternative sites for refugee settlement. The proposed method will be applied to evaluate currently operating temporary accommodation sites in Greece. © Springer International Publishing AG, part of Springer Nature 2018.
URI: https://hdl.handle.net/11499/10976
https://doi.org/10.1007/978-3-319-90315-6_2
ISBN: 18651348 (ISSN)
9783319903149
Appears in Collections:Mühendislik Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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