Prakash, Surya (2019) Emergency relief goods transportation strategies – a Monte Carlo simulation approach. [Conference Proceedings]
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Abstract
A road transportation network and its strategic utilization has a crucial role in emergencies occurring after natural disasters. After most natural disasters, such as floods, hurricanes, tornadoes, earthquakes and tsunamis, one of the most important emergency responses is to provide or deliver relief goods, such as water, food or medicinal supplies, to the affected areas. The complication is that in determining the routes to take for deliveries to affected areas, one has to take into consideration, at the very least, the costs, duration of trips and the availability of the routes. Also the supply and demand situation of the relief goods has to be taken into consideration before choosing the most preferred routes for the deliveries. In this paper, a Monte Carlo approach is applied for the emergency relief goods transportation strategy problem. Monte Carlo simulation has been used for varied applications in including project cost estimation, project schedule estimations, risk assessments, benefit cost analysis and selecting risk response strategies. The Monte Carlo model developed in this paper integrates costs, duration of routes and availability together with the supply and demands requirements to generate the most preferred routes. The results of the Monte Carlo simulations can be used by decision makers (emergency response team) to facilitate the decision making process while choosing the preferred and practical combinations of routes for various deliveries. The proposed approach is then applied to several simple situations to illustrate the simplicity, versatility and practicality of the approach.
| Item Type: | Conference Proceedings |
|---|---|
| Subjects: | H Social Sciences > HE Transportation and Communications Q Science > Q Science (General) |
| Divisions: | Faculty of Science, Technology and Environment (FSTE) > School of Computing, Information and Mathematical Sciences |
| Depositing User: | Surya Prakash |
| Date Deposited: | 07 Oct 2020 23:57 |
| Last Modified: | 07 Oct 2020 23:57 |
| URI: | https://repository.usp.ac.fj/id/eprint/12329 |
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