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Relief chain planning and management: Modeling and analyzing humanitarian logistic problems

Posted on:2009-05-15Degree:Ph.DType:Dissertation
University:University of WashingtonCandidate:Balcik, BurcuFull Text:PDF
GTID:1446390002497706Subject:Engineering
Abstract/Summary:
Despite the stakes and size of the relief industry, the study of humanitarian relief (supply) chains has received little attention and hence quantitative methods and principles that consider the unique characteristics of this domain have not been widely developed. This study is motivated by the needs of relief organizations to develop and implement systematic tools that will enable them to manage their relief chain and logistics operations. We address three critical areas in humanitarian relief chain management: performance measurement, facility location, and last mile distribution. First, we focus on performance measurement and develop performance metrics and a performance measurement framework, which can be used as a basis for a performance measurement system in the relief sector. Secondly, we consider a strategic network design problem, in which facility location and stock pre-positioning decisions are addressed. We develop a variant of maximal covering location model that integrates facility location and inventory decisions and considers various aspects related to strategic relief supply pre-positioning. We present a computational analysis that demonstrates the effects of pre- and post-disaster relief funding on relief system performance, in terms of response time and the proportion of demand satisfied. Finally, we consider the last mile distribution problem in humanitarian relief and develop an analytical approach that will support relief practitioners in making local distribution decisions. In particular, we propose a modeling approach that determines cost-efficient delivery schedules and routings for vehicles while achieving equitable aid distribution. To solve the model in reasonable times, we develop a heuristic based on Simulated Annealing for the last mile distribution problem. We show that the Simulated Annealing algorithm provides good solutions to large problems.
Keywords/Search Tags:Relief, Humanitarian, Last mile distribution, Problem, Performance measurement
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