The robust decision-making framework (RDM) has been extended to consider multiple objective functions and scenarios. However, the practical applications of these extensions are mostly limited to academic case studies. The main reasons are: (i) substantial cognitive load in tracking all the trade-offs across scenarios and the interplay between uncertainties and trade-offs, (ii) lack of decision-makers’ involvement in solution generation and confidence. To address these problems, this study proposes a novel interactive framework involving decision-makers in searching for the most preferred robust solutions utilizing interactive multiobjective optimization methods. The proposed interactive framework provides a learning phase for decision-makers to discover the problem characteristics, the feasibility of their preferences, and how uncertainty may affect the outcomes of a decision. This involvement and learning allow them to control and direct the multiobjective search during the solution generation process, boosting their confidence and assurance in implementing the identified robust solutions in practice.

中文翻译：

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让决策者指导寻找稳健的解决方案：在深度不确定性下进行多目标稳健优化的交互式框架


稳健决策框架 （RDM） 已扩展为考虑多个目标函数和场景。然而，这些扩展的实际应用主要限于学术案例研究。主要原因是：（i） 在跟踪不同情景的所有权衡以及不确定性和权衡之间的相互作用时，认知负荷很大，（ii） 决策者缺乏对解决方案生成和信心的参与。为了解决这些问题，本研究提出了一种新的交互式框架，让决策者利用交互式多目标优化方法寻找最受青睐的鲁棒解决方案。拟议的交互式框架为决策者提供了一个学习阶段，以发现问题特征、他们偏好的可行性以及不确定性如何影响决策结果。这种参与和学习使他们能够在解决方案生成过程中控制和指导多目标搜索，从而提高他们在实践中实施已确定的稳健解决方案的信心和信心。