Abstract
China is one of the countries suffering from the most disasters in the world, so
national emergency warehouse location is critical for the country to reduce loss resulting
from disasters. Considering that emergency management is more concerned
about effectiveness than efficiency, the paper proposes an emergency warehouse location
problem (EWLP) model—an extension of the classic P-center model, for the
Chinese national emergency warehouse location problem. Some features, including
population distribution, economic condition, transportation, and multi-coverage for
some vital areas, are put into the proposed model, which are characterized with data
gathered from the reality. A Variable Neighborhood Search (VNS) based heuristic
algorithm is developed to solve the extensional model. The computational result
gained is cmopared with current emergency warehouse location planning in China.
It is shown that huge saving can be gained with the guarantee that the rescue resources
could be delivered in time. Moreover, the proposed VNS based algorithm
AbstractChina is one of the countries suffering from the most disasters in the world, sonational emergency warehouse location is critical for the country to reduce loss resultingfrom disasters. Considering that emergency management is more concernedabout effectiveness than efficiency, the paper proposes an emergency warehouse locationproblem (EWLP) model—an extension of the classic P-center model, for theChinese national emergency warehouse location problem. Some features, includingpopulation distribution, economic condition, transportation, and multi-coverage forsome vital areas, are put into the proposed model, which are characterized with datagathered from the reality. A Variable Neighborhood Search (VNS) based heuristicalgorithm is developed to solve the extensional model. The computational resultgained is cmopared with current emergency warehouse location planning in China.It is shown that huge saving can be gained with the guarantee that the rescue resourcescould be delivered in time. Moreover, the proposed VNS based algorithm
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