A dynamic model for disaster response considering prioritized demand points.
This paper addresses the problem of distributing relief supplies after the occurrence of a disaster. We develop a dynamic model to serve demand, while prioritizing the response, according to the level of urgency of demand points. Our model is thought to be applied during a planning horizon and it considers dynamic demand, capacity constraints and priorities. To evaluate the applicability of our model, we use a real case study of a flood occurred in Colombia. We also test the computational solvability of our model and we propose and test different methodologies for solving larger instances of our problem. [ABSTRACT FROM AUTHOR]/nCopyright of Socio-Economic Planning Sciences is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
deprivation cost function to compare models
- Mathematical formulation- demand fill rate as a measure of demand satisfaction at each time- case study based on flodd in Columbia
- (i) accessibility of demand points, (ii) time that people at demand points have been waiting for relief items, and (iii) importance or urgency of each type of relief items.
real case study of a flood occurred in Colombia- mathematical model
set of computational examples
- delivery of pallets of relief products to respond to a disaster, such as a flash flood in a given planning horizon.
development of a dynamic model, focusing on computational methodologies
- model is dynamic to account for changes in its parameters- tested the performance of the model- solvability of the model
-develop a dynamic model to serve demand, while prioritizing the response, according to the level of urgency of demand points- an optimization model for planning the distribution of relief items in a planning horizon taking into consideration priority levels of the affected population
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