0000000000285217
AUTHOR
Katja Kaario
Experiments with classification-based scalarizing functions in interactive multiobjective optimization
In multiobjective optimization methods, the multiple conflicting objectives are typically converted into a single objective optimization problem with the help of scalarizing functions and such functions may be constructed in many ways. We compare both theoretically and numerically the performance of three classification-based scalarizing functions and pay attention to how well they obey the classification information. In particular, we devote special interest to the differences the scalarizing functions have in the computational cost of guaranteeing Pareto optimality. It turns out that scalarizing functions with or without so-called augmentation terms have significant differences in this re…
Mental contents in interacting with a multiobjective optimization program
User psychology aims at understanding human-machine interaction from a psychological point of view. Its ultimate goal is to provide knowledge about human psychological properties for interaction designers. In this article, we are particularly interested in applying the theoretical concepts of mental contents (i.e., the information contents of users’ mental representations), in studying interaction with professional software. The immediate motivation for adopting such an approach arises from problems met in designing interaction processes in multiobjective optimization software. These types of software are meant to support complex thought and decision-making processes and this is why interac…