A fuzzy decision support system for pre-disaster budgeting
by Terry R. Rakes; Jason K. Deane; Loren Paul Rees; David M. Goldberg; Josey Chacko
International Journal of Information Systems and Management (IJISAM), Vol. 1, No. 4, 2018

Abstract: Estimating the potential loss from a disaster can be a difficult task due to the great uncertainty plus a lack of historical data. An integer programming budgeting system is developed for pre-disaster planning and mitigation funding where the loss parameters of the decision model are fuzzy numbers based on expert opinion. It allows for two options for representing the fuzzy numbers: the element with the highest grade of membership (the loss level that the expert feels about most strongly) and the element corresponding to the fuzzy average value at risk (AVaR) (a loss level with minimal support, but devastating consequences). A plan based on weighted preferences provides a compromise, using mitigation strategies based on maximum membership and strategies based on AVaR. Comparisons are made to illustrate how the budgeting model could be used to determine the best combination of strategies and weights for allocating mitigation dollars to balance overall risk.

Online publication date: Mon, 10-Sep-2018

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