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RESEARCH PRODUCT
Supporting group decision makers to locate temporary relief distribution centres after sudden-onset disasters
Tina ComesTina ComesMatthieu LaurasHossein Baharmandsubject
010504 meteorology & atmospheric sciencesComputer sciencemedicine.medical_treatment0211 other engineering and technologiesStability (learning theory)Distribution (economics)02 engineering and technology01 natural sciencesHumanitarian responseNATURAL DISASTERSupport groupINFORMATION-MANAGEMENT[SPI]Engineering Sciences [physics]NETWORK DESIGNGroup decision-making2015 Nepal earthquakemedicineOPTIMIZATIONVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550Monte Carlo simulation0105 earth and related environmental sciences021110 strategic defence & security studiesCOORDINATIONCOMPLEXDISTRIBUTION MODELbusiness.industrySTOCHASTIC-MODELHumanitarian responseGeologyGeotechnical Engineering and Engineering GeologyRisk analysis (engineering)Multiobjective facility locationPARETO SETbusinessSafety ResearchHUMANITARIAN LOGISTICSSudden onsetdescription
International audience; In the humanitarian response, multiple decision-makers (DMs) need to collaborate in various problems, such as locating temporary relief distribution centres (RDCs). Several studies have argued that maximising demand coverage, reducing logistics costs and minimising response time are among the critical objectives when locating RDCs after a sudden-onset disaster. However, these objectives are often conflicting and the trade-offs can considerably complicate the situation for finding a consensus.To address the challenge and support the DMs, we suggest investigating the stability of non-dominated alternatives derived from a multi-objective model based on Monte Carlo Simulations. Our approach supports determining what trade-offs actually matter to facilitate discussions in the presence of multiple stakeholders. To validate our proposal, we extend a location-allocation model and apply our approach to an actual data-set from the 2015 Nepal earthquake response. Our analyses show that with the relative importance of covering demands, the trade-offs between logistics costs and response time affects the numbers and locations of RDCs considerably. We show through a small experiment that the outputs of our approach can effectively support group decision-making to develop relief plans in disasters response.
year | journal | country | edition | language |
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2020-05-01 | International Journal of Disaster Risk Reduction |