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Every year, natural disasters and humanitarian crises affect approximately 200 million people, requiring the quick movement of goods and people to ease the human suffering and to return the population to some sense of normality. With contributions to humanitarian relief programmes falling short of what is required, programme managers need to become more cost-efficient and do more with less. The field of operational research (OR) has developed many models to help the commercial sector examine current practices and find ways of becoming more cost efficient. However, much of this good practice has not transferred to the humanitarian field. This paper develops a mathematical transshipment multi-commodity supply-chain flow model for use within humanitarian relief operations. A small data set, based on real life data from the South Asian Earthquake of October 2005, is used to validate the model solutions compared to the real life situation. Several variants of the model are developed to add realism and flexibility over a number of possible scenarios. From the variant solutions several recommendations are made to provide guidance on planning for humanitarian relief operations. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Stored only when both papers are in the corpus — 41 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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