A bottom-up risk-based resource allocation methodology to counter terrorism
After September 11th, government officials have begun questioning the appropriateness of the current federal allocation formula to counter terrorism. Newly appointed Secretary Chertoff demanded the development of more rigorous risk-based mechanisms. This paper is one of the first addressing this request by developing the corresponding resource allocation optimisation model based on the current largely accepted rigorous definition of risk and suggesting a practical implementation of a decomposition methodology to solve it. It is shown how the proposed procedure works and can be carried out in practice within the current geographical hierarchical partitioning of the nation in a 'bottom-up' fashion: 'child' subsets provide their 'parents' with piecewise linear relationships indicating the cost-effectiveness of the allocated budget in reducing the overall risk. This information will be sufficient to solve the overall allocation problem. A successful implementation of the methodology would result in reducing the 'barrier' between theory and application, performing a better resource allocation to counter terrorism, ultimately using fewer resources more efficiently to make the nation safer.
Keywords: terrorism, resource allocation, decomposition, risk, game theory, optimisation, counter terrorism