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

机译:通过二元决策图对风险环境下的投资进行最佳决策

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摘要

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.
机译:本文介绍了在受限风险环境中支持投资和资源分配的两种方法。这些方法基于逻辑决策树和二进制决策图的应用,该方法允许对定性研究进行定量分析。本文考虑的场景是风险环境下的决策过程,其中考虑了随机变量。引入了两种新颖的过程以促进资源分配,将其作为决策过程的目标。第一个过程使用二进制决策图提供的解析表达式作为非线性编程模型的目标函数。第二种方法引入了一种重要度量,该度量考虑了一些外部约束,这与仅考虑树的拓扑结构的经典重要性度量不同。第一种技术将优化结果,第二种技术将使用更简单的计算来提供近似的结果。

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