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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

The Use of Probabilistic Risk Functions and Linear Penalty Functions for Hospital Evacuation Planning

Soeffker, Ninja 20 November 2014 (has links)
In Bish et al. (2014), two approaches for the generation of hospital evacuation transportation plans were proposed: the minimization of the overall risk and the minimization of the evacuation duration. The resulting evacuation plans differ in terms of overall risk and duration, but also in the evacuation order of patients with different characteristics, the filling of hospital beds, and the assignments of the patients to the various vehicle types. Due to the computational effort of the duration minimization, manipulations of the risk functions for the risk minimization approach were searched in this thesis such that the resulting evacuation plans approach the minimal duration without rules for the assignments of patients to vehicle types. It is possible to create risk functions such that the resulting plans have shorter durations than with the basic risk functions, but the overall risk increases and other properties of the plans change. Furthermore, a new objective function was introduced in this thesis that minimizes an overall penalty function, where penalties are incurred for time intervals in which patients are at the evacuating hospital or being transported. The characteristics of the patients are considered by different weights in the penalty function. For the given problem instance, it is possible to choose penalty factors such that the overall risk is close to the minimal risk or to choose them such that the duration decreases. It is a simple approach with run times that are comparable to the risk minimization approach for the given problem instance. / Master of Science

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