Publication:
Aid allocation for camp-based and urban refugees with uncertain demand and replenishments

dc.contributor.authorAzizi, S.
dc.contributor.authorBozkır, Cem Deniz Çağlar
dc.contributor.authorTrapp, A. C.
dc.contributor.authorKundakcıoğlu, Ömer Erhun
dc.contributor.authorKurbanzade, Ali Kaan
dc.contributor.departmentIndustrial Engineering
dc.contributor.ozuauthorKUNDAKCIOĞLU, Ömer Erhun
dc.contributor.ozugradstudentBozkır, Cem Deniz Çağlar
dc.contributor.ozugradstudentKurbanzade, Ali Kaan
dc.date.accessioned2022-09-20T08:36:50Z
dc.date.available2022-09-20T08:36:50Z
dc.date.issued2021-12
dc.description.abstractThere are 26 million refugees worldwide seeking safety from persecution, violence, conflict, and human rights violations. Camp-based refugees are those that seek shelter in refugee camps, whereas urban refugees inhabit nearby, surrounding populations. The systems that supply aid to refugee camps may suffer from ineffective distribution due to challenges in administration, demand uncertainty and volatility in funding. Aid allocation should be carried out in a manner that properly balances the need of ensuring sufficient aid for camp-based refugees, with the ability to share excess inventory, when available, with urban refugees that at times seek nearby camp-based aid. We develop an inventory management policy to govern a camp's sharing of aid with urban refugee populations in the midst of uncertainties related to camp-based and urban demands, and replenishment cycles due to funding issues. We use the policy to construct costs associated with: (i) referring urban populations elsewhere, (ii) depriving camp-based refugee populations, and (iii) holding excess inventory in the refugee camp system. We then seek to allocate aid in a manner that minimizes the expected overall cost to the system. We propose two approaches to solve the resulting optimization problem, and conduct computational experiments on a real-world case study as well as on synthetic data. Our results are complemented by an extensive simulation study that reveals broad support for our optimal thresholds and allocations to generalize across varied key parameters and distributions. We conclude by presenting related discussions that reveal key managerial insights into humanitarian aid allocation under uncertainty.en_US
dc.identifier.doi10.1111/poms.13531en_US
dc.identifier.endpage4474en_US
dc.identifier.issn1059-1478en_US
dc.identifier.issue12en_US
dc.identifier.scopus2-s2.0-85113175967
dc.identifier.startpage4455en_US
dc.identifier.urihttp://hdl.handle.net/10679/7870
dc.identifier.urihttps://doi.org/10.1111/poms.13531
dc.identifier.volume30en_US
dc.identifier.wos000686922800001
dc.language.isoengen_US
dc.peerreviewedyesen_US
dc.publicationstatusPublisheden_US
dc.publisherWileyen_US
dc.relation.ispartofProduction and Operations Management
dc.relation.publicationcategoryInternational Refereed Journal
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subject.keywordsInventory managementen_US
dc.subject.keywordsHumanitarian aiden_US
dc.subject.keywordsNonlinear optimizationen_US
dc.subject.keywordsStochastic modelingen_US
dc.titleAid allocation for camp-based and urban refugees with uncertain demand and replenishmentsen_US
dc.typeArticleen_US
dspace.entity.typePublication
relation.isOrgUnitOfPublication5dd73c02-fd2d-43e0-9a23-71bab9ae0b6b
relation.isOrgUnitOfPublication.latestForDiscovery5dd73c02-fd2d-43e0-9a23-71bab9ae0b6b

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