Optimal decision-making via binary decision diagrams for investments under a risky environment

This paper presents two methods for supporting investments and resource allocation in a constrained risky environment. These methods are based on the application of logical decision trees and binary decision diagrams as an approach that allows quantitative analysis of a qualitative study. The scenario considered in this paper is a decision-making process under risk environment, where stochastic variables are considered. The two novel procedures are introduced to facilitate the resource allocation as the objective of the decision-making process. The first procedure uses the analytic expression provided by binary decision diagrams as an objective function of a non-linear programing model. The second procedure introduces an importance measure that takes into account some external constraints, unlike the classical importance measures that only consider the topology of the tree. The first technique will optimise the outcomes and the second will provide a good approximation of the outcomes using simpler calculations.