Browsing by Author "Vilkkumaa, Eeva, Assist. Prof., Aalto University, Department of Information and Service Management, Finland"

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Supporting decision making in complex multiobjective problems : Practical tools and experiences from the healthcare context
(2024) Neuvonen, Lauri
School of Business | Doctoral dissertation (article-based)
In many countries, healthcare organizations face increasing pressure for providing more services while at the same time suffering from lack of resources, both problems exacerbated by aging populations. This development highlights the importance of resource efficiency. At the same time healthcare decisions often have to take into account multiple, potentially conflicting objectives and complex dynamics. These overlapping requirements make them an interesting application area for multiobjective optimization tools. Recent developments in both computing power and algorithms have made such tools viable in supporting decision making related to healthcare problems of practical scope. This Dissertation develops multiobjective optimization approaches and explores their use in three practical healthcare decision making problems: i) mitigating the impacts of the COVID-19 epidemic, ii) improving the efficiency of the Finnish colorectal cancer screening program, and iii) designing a hospital network for carrying out hip and knee replacement surgeries. These approaches help accommodate robustness considerations as well as hidden or partial information about the decision-maker's preferences. The overall focus in the approaches is on modeling the problem setting in high enough accuracy for the solutions to provide practical insights, while at the same time being able to leverage multiobjective optimization techniques in finding the most promising solutions. The contributions of this Dissertation are two-fold: First, it presents multiobjective optimization approaches, supported by other analytical techniques, that can be used to develop decision recommendations for real-life, complex healthcare decision making problems. These approaches help generate insights that would have been difficult to obtain without the use of model-based tools. A second, more general contribution of the Dissertation is the demonstration of the usability, challenges, and benefits of multiobjective optimization in supporting decision making in problems of realistic scope in the field of healthcare.