Prepositioning of supplies in preparation for a hurricane under potential destruction of prepositioned supplies
Hurricanes are a type of natural for which it is possible to plan for prepositioning of supplies to improve the efficiency of the post- relief effort. This paper develops a model for prepositioning supplies in such a setting. Our model has a distinguishing feature the possible destruction of supply points during the disaster event. To gain insight into our model, we develop a series of theoretical properties. To test the applicability of our model a series of computational tests are performed. From such tests we conclude that it is possible to solve relatively large instances of the problem utilizing standard optimization software. A methodology based on creation of clusters of demand points is proposed for solving even larger problems. Finally we study sensitivity of the results with respect to key parameters. These investigations provide important policy implications.
A sensitivity analysis was conducted to test the impact of the parameters on our model on three outcomes: total expected costs, number of selected supply points and level of storage of the main distribution area( use of CPLEX to solve the model
Literature review, integer programming modeling
The of our model may be classified into two parts: the first is to be applied before the hurricane occurs. It consists of the selection of SPs (supply points) and their level of storage, which gives the amount of prepositioned units. The second part of our is the planned flow of units after the hurricane.
Modeling
Goal In this paper we develop and test a model to preposition supplies in preparation for a hurricane that considers the possible destruction of relief goods.
Limitation of the model are described (p31) e.g. a realistic case study that incorporates a simulation model would be a useful future research project
The outcome is an integer programming model that yields the location and level of storage for prepositioned supplies.Significant improvements in the total relief cost may be reached by means of prepositioning strategies.
Also a factorial was performed in order to formally identify the significant parameters for our model
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